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The DC-DC converter severs as one of the crucial components in DC microgrid applications. In this paper, a novel low frequency current-mode control strategy is proposed to improve overshoot suppression performance for the boost converter against load current and source voltage disturbances. The control strategy is presented as a cascade dual-loop structure composed of a dynamic current-loop controller with asymmetric saturation and a PI form voltage-loop controller. With the low frequency information of disturbances, the designed dynamic current-loop controller delivers not only promising disturbance suppression but also superior reference current tracking. Simulation and experiment results are provided to illustrate the superiority of the proposed strategy on overshoot suppression. [ABSTRACT FROM AUTHOR]

Phase locked loops for fractional frequency synthesis typically use Digital $\Delta \Sigma $ Modulators (DDSMs) as their divider controllers. Different types and configurations of DDSMs have been presented in the past which have distinctive characteristics in terms of spectral shaping of their quantization errors, spur immunity and implementation costs. This paper presents a family of DDSMs that have provably high spur immunity and low folded noise when used in fractional- ${N}$ frequency synthesizers with polynomial nonlinearities. [ABSTRACT FROM AUTHOR]

This paper presents a cycle by cycle Frequency Shift Keying (FSK) demodulator, able to demodulate a FSK signal with 1% frequency modulation index (MI), in a single cycle. Based on the proposed demodulation scheme, a high rate data transmission link can be established through a high-Q inductive coupling link, breaking the basic tradeoff between the power transfer efficiency (PTE) and data rate in single carrier wireless power and data transfer systems. Designed and simulated with $0.18\mu m$ CMOS process, the proposed FSK demodulator, detects successfully a 5Mbps data with a carrier frequency of 5MHz. A test chip is fabricated in 180nm CMOS technology. Measurement results shows that the demodulator is able to demodulate the cycle-by-cycle modulated FSK signals with low modulation index of 2.5%, with a BER of $1.24\times 10^{-5}$. [ABSTRACT FROM AUTHOR]

Single-electron transistors (SETs) exhibit a unique characteristic of Coulomb oscillation which can find many digital applications with area efficiency. More specifically, both MOS and SET devices can be used to implement XOR gates with almost the same area costs regardless of the number of their inputs, outperforming pure CMOS solutions. As multiple-input XOR gates are abundant in the finite field polynomial multiplication which represents the most frequent computation in elliptic curve cryptosystem, hybrid SET-MOS technology can substantially reduce the area cost for this application. This paper presents polynomial multiplication architectures with hybrid SET-MOS transistors and explores Karatsuba-algorithm based multiplication for further area optimization. Simulations show that the proposed hybrid SET-MOS implementations can typically provide around 37% savings in terms of gate count compared to their traditional CMOS counterparts. [ABSTRACT FROM AUTHOR]

In this paper, the digraph filter design based on directed Laplacian matrix (DLM) and least squares method is presented. First, the eigen-decomposition of DLM is used to define the digraph Fourier transform (DGFT). Then, the spectral properties of DGFT are studied and applied to specify the ideal spectral response of the digraph filter. Next, the coefficients of polynomial and rational digraph filters are determined by the least squares method which minimizes the integral absolute squared errors between ideal response and actual spectral response of filter. The matrix inversion can be used to compute the optimal solution. Finally, the proposed method is compared with conventional design methods to evaluate performance and the signal denoising application examples are demonstrated to show the effectiveness of the designed digraph filters. [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]

This paper presents a comprehensive design space exploration for boosting energy efficiency of a fast Fourier transform (FFT) VLSI accelerator, exploiting several approximate multipliers (AxM) combined with approximate adder (AxA) circuits. The FFT hardware herein presented consists of a fixed-point sequential architecture using a radix-2 butterfly with decimation in time. We explore a set of AxMs – namely Dynamic Range Unbiased (DRUM), Rounding-based Approximate (RoBA), leading one Bit-based Approximate (LoBA), and Truncated approach – jointly with the LOA, ETA-I, CopyA, CopyB, Trunc0, Trunc1 approximate adders. The approximate arithmetic operators are used in the butterfly kernel with exploration of the approximation levels (for the ${L}$ and ${K}$ least-significant bits, respectively, for the AxM and AxA), aiming at discovering the most energy-efficient configuration under a design-time QoR constraint. The mean square error and peak signal-to-noise ratio metrics define which approximate levels combining ${L}$ and ${K}$ variations will enable the FFT to process signals to generate spectrograms without significant losses. Our results show that the LoBA multiplier with $L$ =8 together with the LOA, Trunc1 and Trunc0, at different approximation levels, provide most energy savings with controllable quality degradation, presenting a minimum decrease of 20.2% in power dissipation without degrading the spectrogram generation quality. [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]

This paper presents a tunable new deadtime control circuit providing an optimal delay for power converter optimization. Our method can reduce the deadtime loss while improving the efficiency and power density of a given power converter. The circuit presents a reconfigurable delay element to generate a wide range of deadtime for different power conversion applications with varying loads and input voltages. The optimal deadtime equation for buck converters is derived, and its dependency on the input voltage and load is discussed. Experimental results show that the presented circuit can provide a wide range of deadtime delays, ranging from 9.2 ns to 1000 ns. The power consumption of the presented circuit is measured for different capacitive loads ($\text{C}_{\mathrm {L}}$) and operating frequencies (${f}_{\mathrm {s}}$). The circuit consumed a power between 610 $\mu \text{W}$ and $850~\mu \text{W}$ across the measured deadtime ranges while $\text{C}_{\mathrm {L}} =12$ pF, $\text{V}_{\mathrm {dd}} =3.3$ V, and $\text{f}_{\mathrm {s}}=200$ kHz. The proposed deadtime generator can operate up to 18 MHz when the minimum deadtime of 9.2 ns is selected. The presented circuit occupies an area of $150\mu $ m $\times 260\mu \text{m}$. The fabricated chip is connected to a buck converter to validate the operation of the proposed circuit. The efficiency of a typical buck converter with minimum $\text{T}_{\mathrm {DLH}}$ and optimal $\text{T}_{\mathrm {DHL}}$ at $\text{I}_{\mathrm {Load}} =25$ mA is improved by 12% compared to a converter with a fixed deadtime of $\text{T}_{\mathrm {DLH}} =\,\,\text{T}_{\mathrm {DHL}} =12$ ns. [ABSTRACT FROM AUTHOR]

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This paper presents a filtering power amplifier (PA) with wide bandwidth. A bandpass filter (BPF) using discriminating coupling is first proposed to be utilized as the output matching network (OMN) of PA. Discriminating coupling means that the fundamental and the harmonics of the proposed structure have different coupling coefficients. Thus, the input impedances of the fundamental, second and third harmonics could meet the requirements of the extended continuous mode theory, respectively. Also, good frequency selectivity is obtained. The working principle of discriminating coupling, the filter synthesis theory and the equivalent circuit are utilized to guide the design of the filtering PA. To demonstrate the proposed structure, a compact filtering PA operating at 1.8 GHz is designed. The measured results exhibit good frequency selectivity and high power added efficiency (PAE). More importantly, comparing to the previous filtering power amplifiers (PAs) with good frequency selectivity, the proposed design possesses wide bandwidth of 31.1% with PAE higher than 60%. [ABSTRACT FROM AUTHOR]

In recent years, fast computation, low power, and small footprint are the key motivations for building SNN hardware. The unique features of SNN hardware have not been fully exploited, where the computation speed and energy efficiency of the SNN hardware can be improved according to the sparse spiking and non-uniform traffic of SNN. In this paper, we propose a 5.28-mm $^{2}~4096$ -neuron 1M-synapse energy-efficient digital SNN hardware that can achieve ultra-low energy per synaptic operation of 4.5 pJ. The proposed neuron computing unit is implemented in pipeline architecture to achieve high synaptic processing speed. The proposed spike processing unit can significantly increase the processing speed of the neuron core by $1.9\times $ and $9.4\times $ when the spike injection rate is 50% and 10%, respectively. Besides, the increase in the processing speed of the neuron core leads to a reduction in energy consumption of up to 81.5%. An event-driven clock gating circuit that can reduce the power consumption of the proposed neuron block by more than 70% is proposed in this paper. This paper proposes a supervised STDP+ algorithm for SNN training, and the classification accuracy of the MNIST digits is 89.6% with 73.6% weight sparsity of the output layer. [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]

A 3D architecture made up of a CMOS layer combined with a 3D stack of bipolar memristor crossbar arrays provides an innovative approach to hardware support for utilizing the strength of CMOS combined with the strength of memristors. Memristors have been evaluated for implementing a broad spectrum of applications such as memory, computations, hardware-based security primitives, cryptography, etc., and numerous studies have shown that memristors are desirable candidates for such applications. This paper proposes a novel 3D memristive crossbar architecture (i.e., a stack of memristive crossbar arrays built on top of CMOS substrate) with a specific focus on the way of connecting the crossbar arrays to the CMOS layer. The proposed architecture is configurable and allows restructuring crossbar arrays and creating 1D arrays with adjustable sizes. The proposed architecture enables parallel and pipeline computations where data can move or be processed in planes perpendicular to the stacked crossbar arrays. In addition, the proposed architecture is scalable meaning that stacks of crossbar arrays can be connected without additional overhead. This paper shows examples of implementing a full adder, a 4-bit look-ahead carry generator, and an 8-bit multiplexer. Simulations and area, delay, and power analysis demonstrate the behavior of the proposed 3D circuit. [ABSTRACT FROM AUTHOR]

This index covers all technical items - papers, correspondence, reviews, etc. - that appeared in this periodical during the year, and items from previous years that were commented upon or corrected in this year. Departments and other items may also be covered if they have been judged to have archival value. The Author Index contains the primary entry for each item, listed under the first author's name. The primary entry includes the co-authors' names, the title of the paper or other item, and its location, specified by the publication abbreviation, year, month, and inclusive pagination. The Subject Index contains entries describing the item under all appropriate subject headings, plus the first author's name, the publication abbreviation, month, and year, and inclusive pages. Note that the item title is found only under the primary entry in the Author Index. [ABSTRACT FROM PUBLISHER]

Presents a listing of the editorial board, board of governors, current staff, committee members, and/or society editors for this issue of the publication. [ABSTRACT FROM AUTHOR]

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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]

By their very nature, Spin Waves (SWs) excited at the same frequency but different amplitudes, propagate through waveguides and interfere with each other at the expense of ultra-low energy consumption. In addition, all (part) of the SW energy can be moved from one waveguide to another by means of coupling effects. In this paper we make use of these SW features and introduce a novel non Boolean algebra based paradigm, which enables domain conversion free ultra-low energy consumption SW based computing. Subsequently, we leverage this computing paradigm by designing a non-binary spin wave adder, which we validate by means of micro-magnetic simulation. To get more inside on the proposed adder potential we assume a 2-bit adder implementation as discussion vehicle, evaluate its area, delay, and energy consumption, and compare it with conventional SW and 7 nm CMOS counterparts. The results indicate that our proposal diminishes the energy consumption by a factor of $3.14 \times $ and $6 \times $ , when compared with the conventional SW and 7 nm CMOS functionally equivalent designs, respectively. Furthermore, the proposed non-binary adder implementation requires the least number of devices, which indicates its potential for small chip real-estate realizations. [ABSTRACT FROM AUTHOR]

This paper presents a 1.5-GS/s 6-bit single-channel loop-unrolled successive approximation register (SAR) analog-to-digital converter (ADC) using speculative capacitive DAC (CDAC) switching control technique. The proposed SAR ADC achieves a high sampling rate by eliminating additional delays in typical loop-unrolled SAR ADCs related to settling time constraints in their CDACs. Specifically, the CDACs are duplicated and controlled in speculative ways so that the CDAC outputs passage to their next values before completing the regeneration operation of comparators, thereby improving timing constraints for successive approximations. The switching power overhead from the CDAC speculation is mitigated by introducing an energy-efficient CDAC control technique that produces desired voltage transients with minimal power overheads. The prototype of the proposed SAR ADC is fabricated in a 28-nm CMOS technology and occupies an active area of 0.0038-mm2. The design consumes 5.8 mW from a 1.2-V supply. The ADC achieves 1.5-GS/s sampling frequency with a 31-dB SNDR at a low input frequency and a 28.6 dB at the Nyquist frequency without applying any offset calibration techniques, achieving the highest sampling frequency among the 6-bit single-channel loop-unrolled SAR ADCs reported. [ABSTRACT FROM AUTHOR]

In this paper, a novel constrained switching rule, called “time-triggered logical switching” (TTLS) is considered for switched logical dynamic systems (SLDSs). Compared with the general time-triggered switching, the activation mode of TTLS cannot be arbitrary and is pre-allocated according to the logic operation, which is more practical. The TTLS is described as an LDS, and according to the characteristics of LDS, the stability analysis of SLDSs with TTLS is converted into the stability analysis of SLDSs under the logical switching cycle sequences. Firstly, based on the equivalent algebraic form of SLDSs with TTLS, combining the Lyapunov theory of LDS with average dwell-time method, several sufficient conditions are put forward for ensuring the point stability of the considered SLDSs. Then, by defining the switching cycle invariant subset and constructing a new system, the set stability analysis of the original system is transformed into the point stability analysis of the new system, and further, the obtained results for the point stability analysis are applied to the set stability analysis. At last, the validity of obtained results is illustrated by simulation on gene and protein signaling activity patterns. [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]

This paper investigates the leader-following consensus control problem for a class of nonlinear multiagent systems subject to sensor and actuator faults under a fixed directed graph. First, a fault compensation mechanism is proposed because of multiple faults wherein the adaptive parameters substitute the fault coefficients. Then, the command filtering method is employed to avoid the burst of complexity rendered by the duplicative differentiation of the virtual control signal. Furthermore, the neural networks-based state observers are designed to reconstruct the unmeasurable states of the nonlinear multiagent systems. According to the given design approach, a switching threshold-based event-triggered adaptive fault-tolerant control strategy is developed and ensures all the signals in the closed-loop system are semiglobally uniformly ultimately bounded (SGUUB). Finally, the simulation result is provided to demonstrate the validity of the presented method. [ABSTRACT FROM AUTHOR]

This paper presents a 7-bit digital to phase converter (DPC) for high speed clock and data recovery (CDR) applications which is capable of generating multi-phase clocks at 7-GHz frequency. Fabricated in a standard 65-nm CMOS technology, the design introduces a modified phase interpolator (PI) and a quadrature phase corrector (QPC) to reduce the effect of the circuit imperfections on the DPC’s resolution and linearity. Employing a 14-GHz quadrature reference clock, the DPC achieves DNL/INL of 0.7/6 LSB respectively while consuming 40.5 mW power from 1.05 V supply. [ABSTRACT FROM AUTHOR]

This paper presents a low-power constant subthreshold transconductance reference circuit that produces a constant transconductance by subtracting the output currents of two independent transconductance references. By taking the difference between the output currents of the two independent transconductance references, process, voltage and temperature variations are reduced by minimizing the effects of channel length modulation and drain-induced barrier lowering without relying on feedback to regulate the drain voltage. The proposed reference, fabricated in TSMC’s 130 nm process and testing with off-chip temperature-insensitive resistors, can provide a constant transconductance over a temperature range of −30 to 120°C, and a supply voltage range of 0.5 to 1.7 V. The experimental result of the proposed transconductance reference shows an average variation of ±0.8% over temperature for the entire operating voltage range and an average variation of ±1.97% over voltage for the entire operating temperature range. Through the subtraction, the proposed circuit also shows less variation across process corners compared to the conventional constant transconductance reference. The proposed constant transconductance reference exhibits the highest power efficiency (transconductance over power consumption) amongst the reported constant transconductance references. At 0.5 V, the proposed transconductance reference produces a transconductance of 21.46 $\mu \text{S}$ , while consuming 1.95 $\mu \text{W}$. [ABSTRACT FROM AUTHOR]

High step-up converters are often used in photovoltaic applications due to low voltage of photovoltaic modules. In this paper, a study of several voltage step-up cells added on primary and secondary sides of an isolated dc-dc SEPIC (single ended primary inductor converter) is made, in order to increase its static gain and synthesize a family of converters. To perform this study and select the most appropriate resulting converter, theoretical and comparative analyzes are accomplished. They include a brief description of each converter, tables and curves with relevant information, such as voltage gain, voltage stresses and component count, and the identification of the use of coupled inductor or transformer based on the analysis of dc magnetizing current. Moreover, theoretical analysis and experimental results on a 50 kHz and 200 W prototype of selected isolated SEPIC with voltage doubler cell are presented to validate the proposed topology and concept. [ABSTRACT FROM AUTHOR]

This paper presents a digitally programmable bi-directional 7-bit passive phase shifter in a 65 nm CMOS technology. The core of this passive vector-synthesized phase shifter is a hybrid quadrature generator (HQG), an interstage matching network, and a passive vector modulator (PVM). This work proposes a high coupling-factor-based quadrature generator design methodology and demonstrates it with a compact vertical transformer. The interstage matching network between HQG and PVM is proposed to release the bandwidth bottleneck and achieve a 34% fractional frequency bandwidth. Two 6-bit X-type attenuators in the I and Q path form a high-resolution 12-bit controlling word. In 32–40 GHz, this 7-bit 360° phase shifter achieves a measured 2.8° step with 0.45-1.6° RMS phase error and 0.2-0.36 dB RMS magnitude error. With the broadband technique, its 3-dB bandwidth reaches 30.2-42.7 GHz with a 2.8° RMS phase error. Its in-band 1-dB compression point is 10.2 dBm. With the proposed compact HQG and PVM, this mm-wave passive phase shifter only occupies $220\times 630\,\,\mu \text{m}^{2}$ and has no power consumption. [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]

When deploying deep neural networks (DNNs), edge devices training is practical to improve model adaptivity for various user-specific scenarios while avoiding privacy disclosure. However, the training computation is intolerable for edge devices. It inspires sparse DNN training (SDT) into the limelight, which reduces training computation by dynamic weight pruning. Generally, SDT has two strategies based on the pruning granularity: the structured or the unstructured. Unfortunately, both of them suffer from limited training efficiency due to the gap between pruning granularity and hardware implementation. The former is hardware-friendly but has a low pruning ratio, indicating limited computation reduction. The latter has a high pruning ratio, but the unbalanced workload decreases utilization and irregular sparsity distribution causes considerable sparsity processing overhead. This paper proposes a software-hardware co- design to bridge the gap for improving the efficiency of SDT. On the algorithm side, a sub-structured pruning method, achieved with hybrid shape-wise and line-wise pruning, generates a high sparsity ratio and keeps the hardware-friendly property. On the hardware side, a sub-structured weight processing unit (SWPU) effectively handles the hybrid sparsity with three techniques. First, SWPU dynamically reorders the computation sequence with hamming-distance-based clustering, balancing the irregular workload. Second, SWPU performs runtime scheduling by exploiting the feature of sub-structured sparse convolution through a detect-before-load controller, which skips redundant memory access and sparsity processing. Third, SWPU performs sparse convolution by compressing operands with spatial disconnect log-based routing and recovers their location with bi-directional switching, avoiding the power-consumed routing logic. Synthesized with 28nm CMOS technology, SWPU can enable 0.56V-to-1.0V supply voltage with a maximum frequency of 675 MHz. It achieves a 50.1% higher pruning ratio than structured pruning and $1.53\times $ higher energy efficiency than unstructured pruning. The peak energy efficiency of SWPU is 126.04TFLOPS/W, outperforming the state-of-the-art training processor by $1.67\times $. When training a ResNet-18 model, SWPU reduces $3.72\times $ energy and offers $4.69\times $ speedup than previous sparse training processors. [ABSTRACT FROM AUTHOR]

In this paper, global event-triggered adaptive prescribed tracking output feedback control is investigated for a class of nonlinear uncertain systems with unknown control direction. Different from the existing works, the design of the tracking error-dependent normalized function and prescribed boundary is based on our uniformly defined blow-up function rather than a specific function, and the asymmetric constraint requirements on tracking error can be achieved by appropriately selecting the blow-up function. By utilizing the Kalman filter ($K$ -filter) and dynamic gain technique, a new reduce-order observer is proposed, which can make the estimated error exponentially converge to zero. In addition, by introducing a dynamic signal into the trigger condition, a novel event-triggered mechanism is proposed, which can extend the trigger time interval and completely counteract the event-triggered errors in terms of asymptotic stability by sacrificing part of the system transient performance. Furthermore, an adaptive controller is designed based on the backstepping method, which ensures the boundedness of the state of the closed-loop system, while regulating the tracking error meets the global prescribed performance requirements and approaches to zero asymptotically. Two examples are given to illustrate the effectiveness of the proposed control scheme. [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]

Deep learning training involves a large number of operations, which are dominated by high dimensionality Matrix-Vector Multiplies (MVMs). This has motivated hardware accelerators to enhance compute efficiency, but where data movement and accessing are proving to be key bottlenecks. In-Memory Computing (IMC) is an approach with the potential to overcome this, whereby computations are performed in-place within dense 2-D memory. However, IMC fundamentally trades efficiency and throughput gains for dynamic-range limitations, raising distinct challenges for training, where compute precision requirements are seen to be substantially higher than for inferencing. This paper explores training on IMC hardware by leveraging two recent developments: (1) a training algorithm enabling aggressive quantization through a radix-4 number representation; (2) IMC leveraging compute based on precision capacitors, whereby analog noise effects can be made well below quantization effects. Energy modeling calibrated to a measured silicon prototype implemented in 16 nm CMOS shows that energy savings of over $400\times $ can be achieved with full quantizer adaptability, where all training MVMs can be mapped to IMC, and $3\times $ can be achieved for two-level quantizer adaptability, where two of the three training MVMs can be mapped to IMC. [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]

Edge device deep neural network (DNN) training is practical to improve model adaptivity for unfamiliar datasets while avoiding privacy disclosure and huge communication cost. Nevertheless, apart from feed-forward (FF) as inference, DNN training still requires back-propagation (BP) and weight gradient (WG), introducing power-consuming floating-point computing requirements, hardware underutilization, and energy bottleneck from excessive memory access. This paper proposes a DNN training processor named PL-NPU to solve the above challenges with three innovations. First, a posit-based logarithm-domain processing element (PE) adapts to various training data requirements with a low bit-width format and reduces energy by transferring complicated arithmetics into simple logarithm domain operation. Second, a reconfigurable inter-intra-channel-reuse dataflow dynamically adjusts the PE mapping with a regrouping omega network to improve the operands reuse for higher hardware utilization. Third, a pointed-stake-shaped codec unit adaptively compresses small values to variable-length data format while compressing large values to fixed-length 8b posit format, reducing the memory access for breaking the training energy bottleneck. Simulated with 28nm CMOS technology, the proposed PL-NPU achieves a maximum frequency of 1040MHz with 343mW and 5.28mm $\mathbf {^{2}}$. The peak energy efficiency is 3.87TFLOPS/W for 0.6V at 60MHz. Compared with the state-of-the-art training processor, PL-NPU reaches $3.75\times $ higher energy efficiency and offers $1.68\times $ speedup when training ResNet18. [ABSTRACT FROM AUTHOR]

This paper proposes CMOS synapse and neuron for use in spiking neural networks to perform cognitive functions in a bio-inspired manner. The proposed synapse can trace the eligibility of the timing relationship between pre- and post-synaptic spikes, supporting a bio-plausible local learning rule called the spike timing-dependent plasticity (STDP) in an energy- and area-efficient manner. The proposed neuron can support neural functions such as synaptic current integration, threshold-based firing, neuronal leaking, membrane potential resetting, and adjustable refractory period with improved energy and area efficiency. The STDP curve shape of the synapse and the firing rate of the neuron can be adjusted as desired. Their variability due to process, voltage, and temperature (PVT) variations can also be minimized. The proposed CMOS neuron and synapse circuits were designed in a 28-nm CMOS process. The performance evaluation results indicate that the proposed synapse reduces energy consumption and area by up to 94% and 43% compared to conventional CMOS synapses. They also indicate that the proposed neuron achieves energy and area reductions of 37% and 23%, respectively, compared to conventional CMOS neurons. An associative neural network composed of the proposed neuron and synapse was designed to verify that they together work well for performing a cognitive function of associative learning and inferencing. [ABSTRACT FROM AUTHOR]

In this paper, the consensus problem for a class of second-order multi-agent systems under aperiodically intermittent communication is investigated. First, a new sampled-hold-based intermittent control protocol is designed to achieve consensus and improve the consensus performance in the absence of continuous communication. Then, some necessary and sufficient conditions are obtained for second-order consensus based on the relationship of the control gains, the eigenvalues of the Laplacian matrix, and the intermittent communication architecture. Moreover, if the sampled-hold-based aperiodically intermittent control is degenerated into the aperiodically intermittent control or the sampled-hold-based periodically intermittent control, some simpler consensus conditions are also given. Finally, some experimental simulations are shown to verify the correctness of the theoretical analysis. [ABSTRACT FROM AUTHOR]

This paper studies the prescribed-time input-to-state stabilization problem of normal nonlinear systems. With the help of some key properties of a class of parametric Lyapunov equations, the prescribed-time input-to-state stabilization problem of normal nonlinear systems under matched uncertainties is studied. Some bounded time-varying controllers are proposed. It is shown that the closed-loop systems are prescribed-time input-to-state stable. Finally, the effectiveness of the established methods is illustrated by two physical systems. [ABSTRACT FROM AUTHOR]

This paper presents a single-stage tri-path buck converter with reduced inductor current and self-balanced flying capacitor voltage. The proposed converter introduces capacitor paths to reduce the average inductor current and inductor current ripple, hence decreasing the conduction loss. Operating with two states per conversion cycle, it exhibits a relatively low voltage conversion ratio of ${D}$ /(1 $+\,\,2{D}$). Besides, it realizes a self-balanced flying capacitor voltage in the charge redistribution phase. Similar to the conventional buck converter, the proposed converter in continuous-current mode only has two complex poles. Therefore, we design a Type-III compensator to obtain a good transient response. Moreover, the circuit does not require extra supplies for gate drivers due to the reutilization of the flying capacitor voltages, eliminating additional circuit and power overheads. The proposed converter, validated in a 65-nm standard CMOS technology, regulates a 0.7 V – 1 V output voltage from a 3.3 V – 4 V input voltage, delivering a maximum output power of 270 mW. The peak efficiency is 84%, with a switching frequency up to 5 MHz. [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]

Robustness to electromagnetic interference (EMI) is one of the primary design aspects of state of the art automotive ICs like System Basis Chips (SBCs) which provide a wide range of analog, power regulation and digital functions on the same die. One of the primary sources of conducted EMI on the Local Interconnect Network (LIN) driver output is an integrated switching DC-DC regulator noise coupling through the parasitic substrate capacitance of the SBC. In this paper an adaptive active EMI cancellation technique to cancel the switching noise of the DC-DC regulator on the LIN driver output to ensure electromagnetic compatibility (EMC) is presented. The proposed active EMI cancellation circuit synthesizes a phase synchronized cancellation pulse which is then injected onto the LIN driver output using an on-chip tunable capacitor array to cancel the switching noise injected via substrate. The proposed EMI reduction technique can track and cancel substrate noise independent of process technology and device parasitics, input voltage, duty cycle and loading conditions of the DC-DC switching regulator. The EMI cancellation system is designed and fabricated on a 180nm Bipolar-CMOS-DMOS (BCD) process with an integrated power stage of a DC-DC buck regulator at a switching frequency of 2MHz along with an automotive LIN driver. The EMI cancellation circuit occupies an area of 0.7 mm2, which is less than 3% of the overall area in a standard SBC and consumes 12.5 mW of power and achieves 25 dB reduction of conducted EMI in the LIN driver output’s power spectrum at the switching frequency and its harmonics. [ABSTRACT FROM AUTHOR]

This paper presents a new technique of radio frequency (RF) signal strength detection with a received signal strength indicator (RSSI) circuit which can be deployed in an internet-of-things (IoT) network. The proposed RSSI circuit is based on a direct conversion of RF to digital code indicating the signal strength. The direct conversion is achieved by the repeated switching of a rectifier’s output voltage using an ultra-low power comparator. A 5-bit programmable feedback circuit is used to correct detection inaccuracies. The RSSI circuit is implemented in a 65-nm CMOS process and consumes 6nW power. It has a linear dynamic range of 26dB and exhibits an error of ± 0.5dB with a wide bandwidth of 750MHz. A detailed analysis of the RSSI circuit is presented and verified with simulation and measurement results. The high detection accuracy with ultra-low power consumption of our RSSI circuit is favourable for IoT applications including localization, beamforming, hardware security and other low-power applications. [ABSTRACT FROM AUTHOR]

Recurrent Neural Networks (RNNs) have emerged as one of the most popular neural networks for processing time-series problems, widely used in machine translation, automatic speech recognition, and other natural language processing applications. However, conventional RNNs suffered from vanishing and exploding gradients, resulting in poor network performance in applications with long-term input information. As a variant of RNN, Long Short-Term Memory (LSTM) had been proposed to tackle this issue. Nevertheless, at the same time, LSTM introduces gating units and many additional parameters, which makes it challenging to be implemented directly on resource-limited platforms, such as Field Programmable Gate Arrays (FPGAs). This work first investigated the overall maximum achievable compression rates of different gating units and their correlations. Then, Gating Units Level Balanced Compression (GBC) strategy is proposed. After Top- $k$ pruning, the proposed GBC strategy can attain a compression rate of $36.6\times $ for LSTM. Further, the theoretical analysis indicates that for the existing gating units level LSTM compression variants, the GBC strategy still has further potential for compression. A complementary compression of the GBC strategy is performed on the existing coupled-gate LSTM to verify the analysis. Experimental results show that GBC achieves an additional $32\times $ (overall $42.7\times $) compression rate with negligible accuracy loss. Finally, hardware experiments conducted on Xilinx ADM-PCIE-7V3 FPGAs also demonstrate that the accelerator designed in this paper achieves an improvement of 7.4%-191.5% in energy efficiency compared to the state-of-the-art designs. [ABSTRACT FROM AUTHOR]

This paper presents an analog front-end (AFE) circuit with marked timing point for pulsed time-of-flight LiDAR that employs either sampling- or event-based timing approach. The proposed AFE adopts a dual-mode structure for its pre-amplifier which can be configured as a charge-sensitive amplifier (CSA) or a gated active load-assisted TIA (GALA-TIA), depending on the intensity of input current. As a result, both the sensitivity and dynamic range (DR) of the AFE have been effectively improved. In addition, the zero-crossing point of the output signal has been marked as the timing point with a built-in pulse shaper, which allows the back-end circuits of LiDAR receiver discriminate the timing conveniently and accurately. The measured input-referred RMS noise current of the proposed AFE is 37 nA. With dual-mode control, a linear output DR of 80 dB and a wide timing DR of 96 dB with walk error no more than ±160 ps have been achieved. For single-shot measurement application, only CSA mode was enabled and the pulse widths of saturated output signals have been measured to compensate the walk errors, which realized a timing DR of 78 dB with accuracy of ±150 ps. The averaged power consumption is 66 mW and the total silicon area is $0.79\times 0.42\,\,mm^{2}$ in 0.18- $\mu \text{m}$ CMOS process. [ABSTRACT FROM AUTHOR]