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This paper provides a comprehensive study of signal integrity issues in RRAM-based neuromorphic chip crossbar arrays due to interconnect parasitic. First, the parasitic parameters of the crossbar array are calculated by the partial equivalent element circuit (PEEC) method with an efficient unit-cell approach. Numerical experiments show that for a $50\times 50$ array scale, this method consumes only 1.5% of the calculation time of the commercial software based 3D model, which translates to a calculation speed up of 72 times. Moreover, the PEEC circuit simulation results match well with those of the 3D model. Then, we investigate the effects of parasitic parameters such as capacitance and inductance, as well as the feature size of the crossbar array on signal integrity. All of them will lead to corresponding changes in parasitic effects, which in turn result in the most common signal integrity issues such as crosstalk, time delay and mutual capacitive coupling induced sneak path problem. Different from other studies, the excitation used in this paper is the neural spike signal generated by the Izhikevich neuron model, which is both rich in dynamic characteristics and high in computational efficiency. Finally, based on the study we propose a simple but effective design scheme for reduction of signal distortion, which can provide valuable design guidance for neuromorphic systems to achieve high performance and high computational accuracy. [ABSTRACT FROM AUTHOR]

A well-performed capacitive power transfer (CPT) system highly depends on its compensation to achieve load-independent (LI) output and zero phase angle (ZPA) operation. It is particularly meaningful to maintain these objectives under various misalignments. This paper is devoted to a general and comprehensive method to study and explore all the potential high-order compensations. The coupler parameter variation is evaluated under different types of misalignment, and misalignment-insensitive (MI) parameters are properly designed for MI resonance. A general and straightforward decomposition and synthesis method is then proposed to generate the high-order resonant tanks. With the help of inverse ABCD parameters, all tank candidates are further judged by their capability for LI output and ZPA operation. Finally, two example CPT systems are built to verify the LI output and ZPA operation under misalignment. [ABSTRACT FROM AUTHOR]

Neural networks (NNs) with large scales of artificial neurons are increasingly used in recognition and classification tasks. In power-constrained scenarios, the tradeoff between performance and hardware consumptions must be carefully evaluated before silicon tape-out. In this paper, we proposed a systematic approach to design ultra-low power NN system. This work is motivated by the facts that NNs are resilient to approximation in many of the computations and NNs are outputting statistical tensors which are acceptable to less-than-perfect results. We resort to the front-back end approach with a twofold aim: (1) a fast and accurate design approach is proposed by estimating the computing quality of low-power approximate adder arrays, and it is adopted to evaluate the neural network system; (2) a quality configurable engine with different approximation degrees while processing NNs is implemented. The proposed work is demonstrated with a comprehensive keyword spotting (KWS) system as an ultra-low power NN engine. The experimental environment is setup with ten keywords from the google speech command dataset (GSCD) using an industrial 22-nm ultra-low-leakage (ULL) process. Comparing to the state-of-the-art KWS processors, the proposed approximate NN engine can demonstrate over 60% improvement in power efficiency and $1.1\times $ area efficiency while achieving similar recognition accuracy. [ABSTRACT FROM AUTHOR]

Discrete Fourier Transform (DFT) and Fast Fourier Transform (FFT) are core components in the field of signal processing. However, in the existing research, there is no fully analog circuit that can realize the one-step calculation of FFT. Therefore, in this paper, an analog circuit that can calculate FFT and its inverse transform IFFT in one-step is proposed. First, a circuit that can realize complex number operations is designed. On the basis of this structure, a fully analog circuit that can realize fast and efficient computing of FFT and IFFT in one-step is proposed. In addition, different coefficient matching can be obtained to achieve arbitrary points of FFT and IFFT by adjusting the resistance value of the memristor, which has good programmability. Specific examples are given in the paper to evaluate the proposed method. The PSPICE simulation results show that the average accuracy is above 99.98%. More importantly, the calculation speed has been greatly improved compared with MATLAB simulation. Finally, the proposed circuit can be used to quickly solve convolution operation, and the average accuracy can reach 99.95%. [ABSTRACT FROM AUTHOR]

This paper studies stability of stochastic impulsive switched systems. Different from exponential Lyapunov function and average dwell-time in the previous works, general Lyapunov function and fixed dwell-time are implemented in this paper to analyze input-to-state stability and global stability of stochastic impulsive switched systems. Two cases are investigated, that is, the case that the continuous dynamics is stable and the case that the discrete dynamics is stable. To implement multiple Lyapunov functions, there are two subcases considered in this paper: the subcase that the estimates on the derivatives of the multiple Lyapunov functions are the same and the subcase that the growths of the multiple Lyapunov functions by the jumps are the same. For aforementioned different cases, sufficient stability conditions are established for stochastic impulsive switched systems. Finally, the developed theory is illustrated through examples from networked control systems and synchronization problem of 3-D novel chaotic circuit systems. [ABSTRACT FROM PUBLISHER]

This paper proposes a hybrid dynamic model of thyristor controlled series compensators (TCSCs). The objective is to demonstrate, through advanced circuit theory tools and numerical simulations that some modeling aspects are not properly taken into account in the existing literature. In particular, we consider those related to the role of the TCSC impedance when the line current is polluted by harmonics and to the phase-locked loops (PLLs). Shooting methods and periodic small signal analyses are utilized to compute the impedance of the TCSC at sub-harmonics that are typical of the sub-synchronous resonance phenomenon. The case study focuses on the impact of sub-harmonics, on the behavior of the TCSC and on the synchronization of the firing angle through the PLL. Modeling recommendations are finally drawn based on the results presented in this paper. [ABSTRACT FROM PUBLISHER]

This paper studies the process scalability of pulse-mode CMOS circuits for analog 2-D convolution in computer vision systems. A simple, scalable architecture for an integrate and fire neuron is presented for implementing weighted addition of pulse-frequency modulated (PFM) signals. Sources of error are discussed and modeled in a detailed behavioral simulation and compared with equivalent transistor-level simulations. Next, the design of a 180-nm PFM chip with programmable weights is presented, and full image convolutions are demonstrated with the analog hardware. Preliminary chip measurements for a 45-nm implementation are also included to demonstrate process scalability. Design considerations for porting this architecture to nanometer processes, including FinFET technologies, are then discussed. This paper concludes with a simulation study on scaling down to 10 nm using a predictive technology model. [ABSTRACT FROM AUTHOR]

In this paper, we propose a scheme to design the reconfigurable filtering power divider with arbitrary operating channels based on external quality factor ($Q_{\mathbf {e}}$) control. By using an input feeding line, ${n}$ resonators, and $m$ output feeding lines, the $n^{\mathbf {th}}$ -order $m$ -way filtering power divider topology can be obtained with a simple configuration. A coupled-line output feeding structure loading with multiple PIN diodes is proposed to adjust the output $Q_{\mathbf {e}}$ values. Design theories for obtaining the desired $Q_{\mathbf {e}}$ values are provided. Then, the filtering power divider can be fully reconfigured in the states with one to $m$ operating channels. Good input matching can be achieved without using an additional reconfigurable impedance matching network in all these states, resulting in a size and loss reduction. For verification, a 2nd-order 4-way reconfigurable filtering power divider is designed, fabricated, and measured. As compared to the reported reconfigurable power dividers, the proposed design shows the merits of fully reconfigurable operating channels, favorable filtering responses, low insertion losses, high isolation, and a simple structure. [ABSTRACT FROM AUTHOR]

Most memristor-based associative memory neural networks are focused on classical conditioning and ignored operant conditioning. In this paper, a memristor-based neural network of operant conditioning accorded with biological feature is designed. The designed circuit includes a voltage control module, an operant module and synapse modules. It realizes learning, forgetting, long-term memory, reinforcement and punishment functions based on variable synapse structure and double self-protection measure. Meanwhile, the four factors that affect operant conditioning such as contingency, immediacy, magnitude and deprivation are discussed and implemented. The simulation results in PSPICE show that the circuit can be used to simulate actual conditioned reflex and complicated applications. The memristor-based neural network circuit of operant conditioning provides more references for further development of neural networks. [ABSTRACT FROM AUTHOR]

The integral nonlinearity of digital-to-analog converters manifests itself as adjacent-channel power in RF transmitters. This paper derives compact equations relating these two quantities and verifies the results by simulations. Both current-steering and switched-mode architectures are analyzed. [ABSTRACT FROM AUTHOR]

This paper is concerned with the secure estimation problem for the state of charge of Lithium-ion batteries subject to malicious attacks during the data transmission from sensors to cloud-based battery management system terminal. First, the second-order resistance-capacitance equivalent circuit model, whose parameters are identified by Kalman filter in an off-line manner, is introduced to describe the internal dynamics of lithium-ion batteries. Then, by applying the $\chi ^{2}$ detection mechanism, real-time malicious attacks are first detected and then a secure estimator is designed to suppress the influence of attacks on the estimation performance. An upper bound of the filtering error covariance is determined by solving certain coupled Riccati-like equations, and the filter parameter is obtained by minimizing such an upper bound at each time step. Finally, the validity of the proposed attack detection approach and the effectiveness of the developed estimation scheme are verified by experiment results under Federal Urban Driving Schedule condition. [ABSTRACT FROM AUTHOR]

This paper analyzes the ability to suppress in-band noise power of a regenerative amplifier (RA) operating in the nonlinear regime in response to a continuous wave (CW) input tone. As opposed to the linear regime where a CW tone and the noise floor experience the same transfer function, it is shown that the non-linear saturation behavior of an RA yields different transfer characteristics between a CW tone and noise, ultimately leading to an improvement in the output carrier-to-noise ratio (CNR). This is all thanks to the high gain, narrow bandwidth, and the compressive third-order nonlinearity of the RA. This non-linear noise suppression is first analyzed mathematically using single tones in the frequency domain to represent the signal and the noise. Then, simulation of an RA circuit model is shown to be in excellent agreement with the analytical results. Lastly, a discrete RA has been implemented to experimentally verify the noise-suppression phenomenon. The measurement results clearly demonstrate noise suppression and show an output CNR improvement of up to 3 dB. Potential applications of the RA with noise suppression are also discussed. [ABSTRACT FROM AUTHOR]

Inhomogeneous linear ordinary differential equations (ODEs) and systems of ODEs can be solved in a variety of ways. However, hardware circuits that can perform the efficient analog computation to solve them are rarely in the literature. To address such problems, this paper proposes a general method of using a memristor-capacitor (M-C) circuit to solve inhomogeneous linear ODEs and systems of ODEs of any order in initial value problems. The M-C circuit can match the coefficients of the equations sought by adjusting the memristor resistance value according to the coefficient formula proposed in the paper, which has higher programmability. Then, some ODEs and systems of ODEs are given in the paper as examples to evaluate the proposed method. According to the comparison results based on MATLAB software simulation and the simulation based on OrCAD software, the designed M-C circuit has an effective improvement in speed and the accuracy exceeds 99.95% in software simulation. Based on practical verification, this paper gives the actual M-C circuit experiment based on PCB. Moreover, the proposed method can be used to quickly solve the object motion state in the spring mass damping system in actual engineering, and the accuracy can reach 99.98%. [ABSTRACT FROM AUTHOR]

This paper presents a rigorous transfer function analysis of the power supply rejection ratio (PSRR) of low-dropout (LDO) regulators and the LDO with the feed-forward ripple cancellation (FFRC) scheme. Four main noise sources of conventional LDOs are first clarified. An efficient and accurate model is proposed to facilitate the analysis, and the transfer function, along with the poles and zeros, is derived based on the simplified model. Software simulation results and numerical plots are both demonstrated and compared to verify the analytical results, with respect to two specific design examples. The widely-used FFRC scheme for PSRR enhancement is also reinvestigated based on the proposed model. With the inclusion of the FFRC circuit, the new transfer function with new poles and zeros is presented. The working principles of the FFRC scheme are illustrated and the optimal FFRC case is clarified. The proposed model and the derived transfer function match well with the simulation results and the measurement results in prior works. The proposed model and the analytical results serve as the theoretical foundation of the design of high-PSRR LDOs. The recommended simulation methodology could be helpful during the circuit design phase. [ABSTRACT FROM AUTHOR]

In analog fault simulation, the number one challenge is that simulation time could grow rapidly and become prohibitive as the circuit size becomes large. This paper proposes a systematic method to significantly improve the time efficiency in estimating the fault coverage for analog fault simulation. In the proposed method, a circuit under test (CUT) is first partitioned into independent sub-circuits. This is accomplished through mapping the circuit into a graph, decomposing the graph into strongly connected components (SCCs), and generating a sub-circuit for each SCC. The impacts of potential faults directly entering a sub-circuit are then simulated and recorded using the sub-circuits, which is expected to be much more time efficient than fault simulation using the whole circuit, which is much larger in size. Finally, the fault detectability at the given test points is evaluated based on the fault impacts and sensitivity among different sub-circuits. As a first step toward quick estimation of fault coverage, this paper focuses on dc tests. Simulation results show that the fault coverage of dc tests can be estimated sufficiently accurately with simulation time being reduced by 10X for the benchmark circuit, or by approximately the number of SCCs. For a much larger circuit, the number of SCCs is expected to be much larger and the time-saving factor will be much larger. [ABSTRACT FROM PUBLISHER]

This paper is concerned with a method for design and analysis of specific neuronal networks, called central pattern generators (CPGs), which produce primary rhythmic patterns in animals. In particular, the paper is focused on synthetic CPGs made up of few basic elements and governing quadrupeds’ gaits and gait transitions, under the control of an external drive. The method combines the principles of bifurcation theory, geometric properties of symmetry, and numerical analysis based on the recently proposed toolbox CEPAGE. The method is applied to two CPGs, one bio-inspired and one purely synthetic. In both the cases, the method provides a way to obtain a desired sequence of gaits by continuously changing a bifurcation parameter related to the external drive. [ABSTRACT FROM AUTHOR]

The series-paralleling technique of dc-dc converters is utilized in various domains of electrical engineering for improved power conversion. Previous studies have proposed and classified the control schemes for the series-paralleled converters. However, they have several restrictions and lack diversity. The purpose of this paper is to propose passivity-based control (PBC) for the diverse output series-parallel connection of dc-dc converters. It is proved that the output series-paralleled converters regulated by PBC are asymptotically stable. The output series-paralleled converters are numerically simulated to confirm the asymptotic stability. PBC is shown to maintain the stability of the output series-paralleled converters with diverse circuit topologies, parameters, and steady-states. The result of this paper theoretically supports the numerical and experimental considerations in the previous studies and justifies the further extension of the series-parallel connection. [ABSTRACT FROM AUTHOR]

This paper presents an extensive study of linear and logistic regression algorithms implemented with 1T1R memristor crossbars arrays. Using a sophisticated simulation platform that wraps circuit-level simulations of 1T1R crossbars and physics-based models of RRAM (memristors), we elucidate the impact of device variability on algorithm accuracy, convergence rate and precision. Moreover, a smart pulsing strategy is proposed for practical implementation of synaptic weight updates that can accelerate training in real crossbar architectures. Stochastic multi-variable linear regression shows robustness to memristor variability in terms of prediction accuracy but reveals impact on convergence rate and precision. Similarly, the stochastic logistic regression crossbar implementation reveals immunity to memristor variability as determined by negligible effects on image classification accuracy but indicates an impact on training performance manifested as reduced convergence rate and degraded precision. [ABSTRACT FROM AUTHOR]

This paper presents a nonlinear analytical model for an inverter-based switched-capacitor Class-D RF power amplifier (SCDPA). The root causes of the SCDPA AMAM and AMPM nonlinearities are studied. The major factors affecting SCDPA nonlinearities are identified as the unequal on-resistances of selected cell and unselected cell. Specifically, time-varying resistance of the switch, different transistor responses during the transition and parasitic resistance on the supply path (IR drop) are analyzed. Then, the system-level result, like EVM and power spectral density, can be obtained with nonlinear behavior of PA. The results of model calculation, schematic simulation, and measurement are presented and compared with validate the model both on transistor level and system level. This paper, for the first time, provides an accurate design guidance to enable fast architecture study and quick circuit-level prototype with close-to-optimum component initial parameters. It can be expanded to more architectures, therefore helps to pave the path to future design automation for highly linear SCDPAs. [ABSTRACT FROM AUTHOR]

Precision oscillators are ubiquitous in modern electronic systems, and their accuracy often limits the performance of such systems. Hence, a deep understanding of how oscillator performance is quantified, simulated, and measured, and how it affects the system performance is essential for designers. Unfortunately, the necessary information is spread thinly across the published literature and textbooks with widely varying notations and some critical disconnects. This paper addresses this problem by presenting a comprehensive one-stop explanation of how oscillator error is quantified, simulated, and measured in practice, and the effects of oscillator error in typical oscillator applications. [ABSTRACT FROM AUTHOR]

This paper studies the automation of the distortion analysis of multistage operational amplifiers by a symbolic analysis. The goal is to generate the readable closed-form design equations that relate the frequency-dependent harmonic distortion (HD) features, such as dc level, corner frequency, peaking, and zero, to the circuit parameters (including the nonlinearity coefficients). Prior research achieved such kind of characterization by carrying out the traditional signal-flow graph (SFG) analysis, which is highly algebra-involved and depends mainly on the manual derivation. This paper achieves automation by formulating a multiport circuit analysis strategy and applying a topological symbolic analysis method as an intermediate step in generating nodal transfer functions. The frequency-dependent HD factors are then characterized by analytically forming proper virtual current sources associated with the nonlinearity of each stage, modeled by a cubic polynomial. Implementation shows that the proposed tool can generate approximate closed-form HD characterization with comparable accuracy to full transistor-level simulation. The proposed automation tool can substantially mitigate heavy manual derivation work required by the existing SFG-based methods. Theory, software implementation, and circuit application are covered in detail. [ABSTRACT FROM AUTHOR]

This paper presents a high-performance solar energy harvesting system with improved adaptive maximum power point tracking (AMPPT) method utilizing neural network (NN) model as assistance. Under the guidance of the negative feedback control (NFC) model, a BJT based voltage control oscillator with three off-chip reconfigurable resistors is designed in this paper to improve the reusability of the solar energy harvesting system. Meanwhile, the AMPPT accuracy has much improvement by co-simulation of MATLAB/Simulink and Virtuoso with the help of NN model of Photovoltaic (PV) Cell. The complete system with output voltage of 4.2V to power the battery is designed and fabricated in $0.18~\mu \text{m}$ CMOS technology. According to the test results, the system can track the maximum power points (MPP) successfully with average voltage tracking errors of 0.23% (0.01-0.51%) of PV cell 1 and 0.29% (0.01-0.5%) of PV cell 2 when the light intensity changes from 3000lux to 10000lux. Without power hungry current sensor or voltage sensor and other complicated control circuits, the peak efficiency is about 89.39% @ 3000lux. [ABSTRACT FROM AUTHOR]

In this paper, a unified framework is proposed to address the synchronization problem of memristor chaotic systems (MCSs) via the sliding-mode control method. By employing the presented unified framework, the finite-time and fixed-time synchronization of MCSs can be realized simultaneously. On the one hand, based on the Lyapunov stability and sliding-mode control theories, the finite-/fixed-time synchronization results are obtained. It is proved that the trajectories of error states come near and get to the designed sliding-mode surface, stay on it accordingly and approach the origin in a finite/fixed time. On the other hand, we develop an image encryption algorithm as well as its implementation process to show the application of the synchronization. Finally, the theoretical results and the corresponding image encryption application are carried out by numerical simulations and statistical performances. [ABSTRACT FROM AUTHOR]

This paper introduces rational polynomial chaos expansions for the stochastic modeling of the frequency-domain responses of linear electrical networks. The proposed method models stochastic network responses as a ratio of polynomial chaos expansions, rather than the standard single polynomial expansion. This approach is motivated by the fact that network responses are best represented by rational functions of both frequency and parameters. In particular, it is proven that the rational stochastic model is exact for lumped networks. The model coefficients are computed via an iterative re-weighted linear least-square regression. Several application examples, concerning both lumped and a distributed systems, illustrate and validate the advocated methodology. [ABSTRACT FROM AUTHOR]

In this paper, we present a compact memristor model for bipolar neuromorphic ReRAM devices. The proposed model focuses on the high level description of the device, and it reproduces some of the most important characteristics (i.e. conductance, energy dissipation) without needing a detailed electrical simulation. Its functionality is shown by using it to model the behavior of three different ReRAM devices that were fabricated and measured at the CNR-IMM, MDM Laboratory. The parameters extraction procedure is also discussed. The obtained results clearly show that the model proposed in this paper is able to capture the influence of the programming pulse parameters (i.e. pulse duration and height) changes. This is accomplished by the introduction of a parameter, which is related to the specific device technology. [ABSTRACT FROM AUTHOR]

The computation-intensive circuit simulation makes the analog circuit sizing challenging for large-scale/complicated analog/RF circuits. A Bayesian optimization approach has been proposed recently for the optimization problems involving the evaluations of black-box functions with high computational cost in either objective functions or constraints. In this paper, we propose a weighted expected improvement-based Bayesian optimization approach for automated analog circuit sizing. Gaussian processes (GP) are used as the online surrogate models for circuit performances. Expected improvement is selected as the acquisition function to balance the exploration and exploitation during the optimization procedure. The expected improvement is weighted by the probability of satisfying the constraints. In this paper, we propose a complete Bayesian optimization framework for the optimization of analog circuits with constraints for the first time. The existing GP model-based optimization methods for analog circuits take the GP models as either offline models or as assistance for the evolutionary algorithms. We also extend the Bayesian optimization algorithm to handle multi-objective optimization problems. Compared with the state-of-the-art approaches listed in this paper, the proposed Bayesian optimization method achieves better optimization results with significantly less number of simulations. [ABSTRACT FROM PUBLISHER]

We reconsider the black box model by Urbanek of electric-arc in air-blast circuit breakers or in circuit breakers characterized by an electro-negative gas (e.g., SF6) as quenching medium. It has the unique characteristic to account for the dielectric breakdown that possibly reignites the arc. We show some of its main features that have been almost hidden from the first publication of the model in the literature. The conductance in the Urbanek model plays two roles: 1) it effectively represents the conductance of the burning arc when positive and 2) it is a thermodynamic indicator when negative. This thermodynamic indicator is used to eventually trigger a restrike of the arc. We show that this switching behavior can be formally analyzed by considering the model as an hybrid dynamical system. In this paper, we reconsider it and show its main dynamic properties through some case studies. [ABSTRACT FROM PUBLISHER]

This paper presents a novel static digital pre-distortion (DPD) method for a current-steering digital-to-analog converter (CS-DAC). The proposed method utilizes the knowledge of the current cell array architecture to calculate the static mismatch currents of the cells. The mismatch values are stored in memory and added to the original input code to generate the new pre-distorted input word. The converter corrects the static error with its own current cells without incorporating an additional calibration DAC (CALDAC) or programmable current sources. This results in a reduction in area, power and simulation run times because of the simpler circuit design. An Overflow-Cell-Selection (OCS) is introduced as a novel solution to further enhance the static linearity of the converter. It also can be implemented as a software solution for already existing DAC designs which do not have an integrated DPD and lab/measurement equipment (e.g., arbitrary wave generator (AWG)). This poses as a strong differentiation factor compared to other state-of-the-art static DPD methods. The evaluation of the proposed DPD is done via simulations in MATLAB and on- chip measurements with a 14-bit CS-DAC in 16 nm. Single tone measurements show a performance gain of the total harmonic distortion (THD) of 12 dB. [ABSTRACT FROM AUTHOR]

Diffusion-driven instabilities with pattern formation may occur in a network of identical, regularly-spaced, and resistively-coupled cells if and only if the uncoupled cell is poised on a locally-active and stable operating point in the Edge of Chaos domain. This manuscript presents the simplest ever-reported two-cell neural network, combining together only 7 two-terminal components, namely 2 batteries, 3 resistors, and 2 volatile NbOx memristive threshold switches from NaMLab, and subject to diffusion-driven instabilities with the concurrent emergence of Turing patterns. Very remarkably, this is the first time an homogeneous cellular medium, with no other dynamic element than 2 locally-active memristors, hence the attribute all-memristor coined to address it in this paper, is found to support complex phenomena. The destabilization of the homogeneous solution occurs in this second-order two-cell array if and only if the uncoupled cell circuit parameters are chosen from the Edge of Chaos domain. A deep circuit- and system-theoretic investigation, including linearization analysis and phase portrait investigation, provides a comprehensive picture for the local and global dynamics of the bio-inspired network, revealing how a theory-assisted approach may guide circuit design with inherently non-linear memristive devices. [ABSTRACT FROM AUTHOR]

This paper presents a hybrid-integrated optical transceiver front-end for beyond-400G short-reach optical links. A pair of the monolithic 8-channel laser drivers and the trans-impedance amplifier (TIA) is developed in 180nm SiGe BiCMOS, incorporating arrayed Vertical-Cavity-Surface- Emitting Lasers and photo-detectors. The driver uses a $2^{\mathrm {nd}}$ -order continuous-time linear equalizer (CTLE) to compensate for the channel loss with a nonlinear frequency response. Both the inductive peaking and RC-degeneration are embedded at the output stage to extend the optical modulation bandwidth (BW). The series-peaking and multi-stage distributed CTLE are combined in a resistive feedback TIA topology for improved BW and linearity. Measurement results show up to 100-Gb/s PAM-4 electrical eyes of the driver and TIA. The optical transmitter front-end operates 56 Gb/s, 4.1-dB extinction ratio, and 6.6-pJ/bit power efficiency, while the optical receiver front-end achieves 56-Gb/s, $10^{-6}$ bit error rate, and 5.9-pJ/bit power efficiency. [ABSTRACT FROM AUTHOR]

An automatic inductor design process is helpful to reduce the design cycle of radio frequency (RF) integrated circuit (IC). This paper proposed an efficient synthesis-analysis machine (SAM) for on-chip inductor synthesis and modeling, as well as an automatic dataset generation (ADG) topology for the generation of artificial neural networks (ANNs) training dataset. The SAM consists of a synthesis ANN, two analysis ANNs and a proposed self-inspection machine (SIM). For a given design request, the SAM synthesizes a layout first, followed by analyzing the performance of the layout automatically, and finally improves the layout confidence through self-inspection. Compared to the modeling functions of analysis ANN, the synthesis ANN behaves as an inverse model, of which the inputs are desired inductor performances while the outputs are geometrical parameters of the layout. However, multi-value problems might occur in obtaining geometries of inductors, suggesting with evidence from mathematic relationships between geometrical and electrical parameters of an inductor. A multi-valued training dataset will mislead the synthesis ANN, resulting in unqualified layouts. To deal with this issue, a solution space contraction technique (SSCM) is also proposed. Furthermore, the SIM suspends most of the failures by comparing the output of analysis ANN back to the input of synthesis ANN. An electromagnetic simulation tool is used for experiments, and the effectiveness of the proposed SAM is proven by 6,500 inductor samples. [ABSTRACT FROM AUTHOR]

Recent studies on integrated circuits interconnections are mainly concentrated on the analysis of crosstalk and delay, by taking the trade-off between accuracy, speed, and complexity into consideration. The new idea of this paper is to apply the convex optimization method to analyze crosstalk and delay of the lossy coupled interconnections in identical and non-identical forms. For this purpose, a simple and comprehensive model is proposed to cover the functional and dynamic crosstalk in a computationally-effective way. More specifically, various case studies are determined to analyze the transient response of the coupled transmission lines with arbitrary excitation sources in the presence of both capacitive and inductive coupling characteristics. To validate the model, the numerical and Advanced Design System (ADS) simulation results are compared to indicate the desired accuracy. The calculated crosstalk percentage error of the proposed model with respect to ADS and HSPICE are less than 1.03% and 1.19%, respectively. In addition, the computational speed of the proposed method is about twice higher than ADS and HSPICE. The proposed model is extendible to handle ${N}$ coupled lines, making it appropriate to model complex integrated circuit interconnections. [ABSTRACT FROM AUTHOR]

Stacked MOS power amplifiers (PA) are commonly used in SOI nodes but also have the potential to be realized in bulk CMOS nodes. In this paper they are analyzed in millimeter wave regimes. The study focuses on the key limiting factors and in particular the optimum number of transistors from which the key performance parameters such as maximum possible operating frequency, output power, and efficiency are achieved. Based on the analysis, design trade-offs of stacked MOS PAs are presented. The frequency dependency of the optimum load presented to each stack is analyzed to express the overall performance of the mentioned PA topologies as a new optimization method. Additionally, it is shown how the optimal load variations translate into amplitude-to-amplitude/phase (AM-AM/PM) conversion distortions. The validity of the analysis is examined against simulations. The simulations are performed based on 8M1P CMOS 28nm technology and electromagnetic simulations in ADS Momentum. [ABSTRACT FROM AUTHOR]

Efficient simulation of switched-mode power conversion circuits is necessary for the analysis and optimization of power electronics. This paper introduces the extended impedance method (EIM) to the simulation and analysis of general switched-mode power converter circuits. By using the EIM method, the conventional impedance concept can be extended to involve more linear time-variant (LTV) and nonlinear devices, such as MOSFET switches and diodes, which are commonly used in switched-mode power conversion circuits. EIM models a circuit network from the component level in the frequency domain, rather than from the system-level constitutive differential equation in the time domain. Compared with the conventional averaging method, EIM can reveal more high-frequency features of a switched-mode converter circuit, in particular, those around the switching instants. A buck converter is taken as a representative example to validate the EIM based analysis. Both the simulation and experimental results prove that EIM provides precise numerical results, which match the real waveform, as the commercial simulators, e.g. PSpice and ADS, do. Moreover, it largely reduces the computational complexity towards more efficient and more flexible steady-state analysis of switched-mode power electronics. [ABSTRACT FROM AUTHOR]

In this paper it is proposed and explored the use of the Dickson charge pump (CP) to amplify time-variant signals. The study has been carried out through a theoretical analysis that provides an in-depth comprehension of the behavioral equations and the main design metrics commonly used to evaluate the performance of amplifiers. Starting from the analytical models, we show the conditions upon which the CP can be modeled with an equivalent small signal circuit and can amplify a signal. Then, assuming the CP working in the widest operative conditions, small-signal, large-signal and noise analysis are carried out. The results have been validated by extensive simulations and measurements on a proof of concept using a 130 nm CMOS technology. [ABSTRACT FROM AUTHOR]

A new approach to augment existing noise models in a relaxation oscillator by including noise spikes during state change, an important aspect hitherto not covered in existing noise models, is proposed. Such noise spike is due to regeneration at the jump and this paper attempts to offer an explanation by viewing state change as a physical phase change in a thermodynamic system, which is also due to regeneration. The connection is established by viewing the relaxation oscillator as a combination of bistable circuit (exhibits metastablility) and a timing capacitor. Similarly the thermodynamic system exhibits physical phase change (metastability). Formula is derived to predict the “magnitude” of the noise spike, as a function of regeneration parameter, and hence design parameter such as gm, R, {I}_{0}. Simulations (Eldo) on circuits and simulations (Metropolis) on thermodynamic system as well as measurements on circuits fabricated in 0.13 \mu$m CMOS technology are consistent with theory. [ABSTRACT FROM PUBLISHER]

This paper presents a novel analysis of nonlinear circuits useful for the computation of the reactive power from only terminal measurements. The method computes the reactive power of unknown circuits based on the physical understanding of Maxwell equations. The proposed method is able to identify instantaneous quantities (circuit parameters, powers, etc.) for two physical equivalent models: series and parallel circuits. The parallel equivalent model shows advantages for multi-subsystems. Several numerical examples are provided for validation of the proposed method and to illustrate step-by-step the calculation details. To be compatible with digital instrumentation, a time discrete formulation is used for all calculations. All examples are simulated in MATLAB and the EMTP (Electro-Magnetic Transients Program). [ABSTRACT FROM AUTHOR]

Silicon Carbide (SiC) MOSFETs are usually paralleled to increase the current capability for high power applications. While, the asymmetrical parasitic parameters of the wide-used laminated busbar can cause current imbalance for paralleled MOSFETs. The fast switching of SiC devices can further deteriorate the imbalance. However, the complex current paths and their mutual effects are seldom considered and effectively modeled for the parasitics of the busbar, which is not accurate enough to evaluate the current imbalance for the busbar connected with SiC devices. This paper proposes accurate modeling of the effective parasitic parameter of laminated busbars with paralleled SiC MOSFETs. The model incorporates not only the self-inductance and resistance but also the complex mutual coupling effect of all the current paths. Moreover, a switching period is divided into two durations for accurate effective parasitic models, in which the busbar can have different effective models regarding one physical structure. Furthermore, for easy evaluation of the current balance, a single effective model, namely equivalent model, is derived for a physical structure by replacing the complex mutual network. A specific laminated busbar for EV inverter is analyzed to prove the above theory, which is validated by simulation and experiment separately. [ABSTRACT FROM AUTHOR]

Tree-based machine learning models, like random forests and decision trees, are low-complexity solutions that provide an efficient prediction for a wide range of applications. These models are particularly interesting for energy-constrained platforms since they can be implemented with simple logical operations. Tree-based accelerators are also intrinsically resilient to errors, and this can be leveraged to boost energy efficiency with approximate computing techniques. The key operations in these models are comparisons to constants, making comparators excellent candidates for approximation. This paper presents a technique to approximate comparisons to constants called C2PAx, which is capable of reducing the area and energy of tree-based accelerators. The method consists in finding alternative constants that reduce circuit area while keeping an efficient prediction performance. It is also shown that the selection of the constant parameters directly influences both hardware complexity and model performance, demanding cross-layer optimization. For that, we extend an existing framework that generates VLSI tree-based accelerators, inserting our approximation proposal that allows selecting the constant parameters that maximize energy efficiency at the cost of minor accuracy drops. Simulation results demonstrate that C2PAx outperforms the Don’t Care logic approximation technique when accuracy and energy are jointly considered. C2PAx trades accuracy for significant reductions in the VLSI area, power, delay, and energy consumption compared to precise models. [ABSTRACT FROM AUTHOR]

Multipliers are essential in implementing nonlinear neuron models, but they take huge implementation costs. Many multiplierless fitting schemes have been proposed to simplify the implementation of nonlinearities in neuron models. To optimize these schemes, this paper presents a nullcline-characteristics- based piecewise linear (NC-PWL) fitting scheme for multiplierless implementations of Hindmarsh-Rose (HR) neuron model. This NC-PWL fitting scheme uses as few line segments as possible to approximate the critical nonlinearity characteristics of the local nullclines. A NC-PWL HR neuron model that reproduces diverse firing patterns of the original one is successfully established. Using off-the-shelf low-cost components, an analog multiplierless circuit is designed for this fitting model and welded on print circuit board (PCB). Meanwhile, by logical shift method, a digital multiplierless circuit with low resource consumption is developed for this fitting model on field-programmable gate array (FPGA) platform. Experimental results of the analog and digital multiplierless hardware implementations verify the numerical simulations and show the simplicity and feasibility of the presented fitting scheme. [ABSTRACT FROM AUTHOR]

In this paper, a miniature dual-band absorptive bandstop filter (ABSF) design with improved lower passband performance is proposed. Specifically, a stepped-impedance short-circuited stub is introduced to a bridged-T coil-based dual-band ABSF design, such that the insertion loss around the desired passband center frequency can be largely reduced while the absorptive stopband performance remains intact. This also helps equalize the lower passband insertion loss response and achieve a flatter passband, which is especially advantageous when cascading multiple ABSFs for improving the stopband rejection or increasing the number of stopbands. Closed-form design formulas are established to facilitate the synthesis of proposed dual-band ABSF. As an example, a 4.8/9.6-GHz dual-band ABSF in GaAs is realized with a measured insertion loss within 0.85± 0.12 dB from dc to 2.6 GHz. The circuit size is only 1.6 mm $\times $ 1.84 mm, and the corresponding electrical size is $0.013\lambda _{0} \times 0.015\lambda _{0}$ at the designated passband center frequency of 2.4 GHz. Application of the proposed dual-band ABSF for the passband performance improvement of cascaded ABSF designs is also demonstrated, and good performance is obtained. [ABSTRACT FROM AUTHOR]

The main focus of this paper is the evolution of complex behavior in a system of coupled nonlinear memristor circuits depending on the applied coupling conditions. Thereby, the parameter space for the local activity and the edge-of-chaos domain will be determined to enable the emergence of the pattern formation in locally coupled cells according to Chua’s principle. Each cell includes a Niobium oxide-based memristor, which may feature a locally active behavior once it is suitably biased on the negative differential resistance region of its DC current-voltage characteristic. It will be shown that there exists a domain of parameters under which each uncoupled cell may become locally active around a stable bias state. More specifically, under these conditions, the coupled cells are on the edge-of-chaos, and can support the static and dynamic pattern formation. The emergence of such complex spatio-temporal behavior in homogeneous structures is a prerequisite for information processing. The theoretical results are confirmed by measurements as well as by the numerical simulations of the accurate device and circuit models. [ABSTRACT FROM AUTHOR]

The topic of this paper is the development of biological models for 3D reaction–diffusion phenomena that can be used in any circuit electronic design automation environment for the simulation of biosensors. Biological systems that involve such 3D phenomena are described by partial differential equations. Our approach consists in discretizing these equations according to the finite-difference method and converting the resulting ordinary differential equations into an assembly of elementary electronic equivalent circuits that are directly simulated with SPICE. The main interest of this approach is the ability to couple such models with third-party SPICE models of electronic circuits, sensors, and transducers, i.e., models from any physical domain ruled by Kirchhoff laws, allowing modeling and simulation of any multi-physics systems in a conventional circuit design environment, here CADENCE. The tool is validated on simple problems for which analytical solutions are known. Then, the interest of the approach is illustrated on the study of a biosensor. [ABSTRACT FROM AUTHOR]

The technology for oxide resistive memories offers nowadays a number of different implementations and solutions. As a consequence, many models have been presented so far, generally technology-specific, representing a problem for the memory design standardization. Moreover, the computational effort can be reduced using memristive models with lower complexity but that grant at the same time good speed and numerical stability. In this paper, the authors try to find a compromise between accuracy and computational costs, proposing a simulation procedure based on a linear approximation of the memristive device model. The description, formally derived from the traditional linear model, has been implemented in Verilog-A and, thanks to the analysis of practical design cases on a reference architecture, has been demonstrated to be useful in highlighting critical parasitic effects related to the interaction of the memristive cells with the memory circuit periphery. Thanks to the approximated method, a computer simulation time saving up to 40% is achieved when simulating a full cross-bar memory device. The model parameters have been extracted from experimental curves obtained from HfO2 devices implemented in a 250-nm BiCMOS IHP technology. [ABSTRACT FROM AUTHOR]

This paper studies an $H_{\infty }$ model reduction problem for interval frequency negative imaginary (IFNI) systems. For a given IFNI system, our goal is to find a reduced-order IFNI system satisfying a pre-specified $H_{\infty }$ approximation error bound over the finite-frequency interval. Necessary and sufficient conditions in terms of matrix inequalities are derived for the existence and construction of an $H_{\infty }$ reduced-order IFNI system. An improved iterative algorithm is provided to solve the matrix inequalities and to minimize the $H_{\infty }$ approximation error. The proposed method is further clarified via the application to the electrical circuits, such as high-order Sallen–Key low-pass filter, piezoelectric tube scanner, and RLC circuit. The simulation results on these electrical circuits are compared with the finite-frequency interval Gramians-based model reduction method both in the frequency domain and time domain. [ABSTRACT FROM AUTHOR]

Ten methods for finding through simulations the small-signal phase and gain margins of feedback circuits based on op-amps are described and analyzed in this mostly tutorial paper. The testbenches employed by these methods are presented and the corresponding analytical expressions of the return ratio are derived and compared against their “ideal” counterpart, obtained with standard circuit analysis; the requirement that the return ratio should not depend on the point it was measured at is also verified. These analyses are performed on a fairly general case: a generic reciprocal two-port network that closes a feedback loop around an op-amp acting as the forward amplifier. The four main types of op-amps were considered. The limitations of some of the tested methods are then highlighted by simulations. Besides the detailed analysis of previously reported methods, the paper proposes a novel method for deriving the return ratio of feedback circuits, that employs only current stimuli; it is demonstrated analytically that this method can be used for bilateral circuits, not only for op-amp-based (unilateral) ones. Also, a recent method for deriving directly the phase margin of a circuit is extended to estimating the gain margin, too. Conclusions on the accuracy and suitability of the analyzed methods for practical circuit cases are drawn. These results are then extended to other circuit topologies. [ABSTRACT FROM AUTHOR]

In this paper, we develop and test a piecewise model for the reset and set transitions of a bipolar ReRAM memristive device in the flux-charge space, instead of the usual voltage–current one. To do so, we consider the devices as memristors. The model used is very simple and provides accurate simulation results. It also allows the development of simple expressions for the conductance and power consumption, as well as the characterization of the ReRAM memristive device in voltage–current domain by using two points for any reset or set cycle. We consider the case of a ramp input signal with different slopes to obtain the model parameters, and we compare the predictions of our model with experimental results. [ABSTRACT FROM AUTHOR]

Sub-harmonic pulse injection-locked oscillators are becoming attractive candidates for the design of clock multipliers and as building blocks of phase-locked loops. Unfortunately, due to the large amplitude of the injected signals, these circuits cannot be analyzed with conventional methods and very-time-consuming simulations are needed to determine their phase noise performance. Phase-noise simulations are particularly critical when the ratio N between the output and the injection frequency gets large. To address the above issue, this paper provides an efficient computation flow to derive the phase noise of pulse injection-locked oscillators. The flow simply requires the computation of the phase-domain response and the phase noise of the free-running oscillator. An analytical expression, herewith demonstrated and compared against commercial simulation tools, allows calculating the phase noise of the injection-locked oscillator for any frequency ratio N. [ABSTRACT FROM AUTHOR]

The twelve papers in this special section were presented at the 2013 IEEE Custom Integrated Circuits Conference (CICC 2013)that was held in San Jose, CA, September 2013. [ABSTRACT FROM AUTHOR]

Flexible electronics is rapidly evolving towards devices and circuits to enable numerous new applications. The high-performance, in terms of response speed, uniformity and reliability, remains a sticking point. The potential solutions for high-performance related challenges bring us back to the timetested silicon based electronics. However, the changes in the response of silicon based devices due to bending related stresses is a concern, especially because there are no suitable models to predict this behavior. This also makes the circuit design a difficult task. This paper reports advances in this direction, through our research on bendable piezoelectric oxide semiconductor field effect transistor (POSFET) based touch sensors. The analytical model of POSFET, complimented with Verilog- A model, is presented to describe the device behavior under normal force in planar and stressed conditions. Further, dynamic readout circuit compensation of POSFET devices have been analyzed and compared with similar arrangement to reduce the piezoresistive effect under tensile and compressive stresses. This approach introduces a first step towards the systematic modeling of stress induced changes in device response. This systematic study will help realize high-performance bendable microsystems with integrated sensors and readout circuitry on ultra-thin chips (UTCs) needed in various applications, in particular, the electronic skin (e-skin). [ABSTRACT FROM PUBLISHER]