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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]

This paper deals with global synchronization problem of multiple discrete-time Markovian jump memristor-based neural networks (DTMJMNNs) with mixed mode-dependent delays via a novel event-triggered impulsive coupling control (ETICC). The parameters of the multiple DTMJMNNs and the mixed time delays (both discrete and distributed delays) switch randomly according to a Markov chain. In the ETICC strategy, the controller does not work all the time, but only works at impulse instants determined by specific events. In particular, the coupling matrix can be non-Laplacian. By using the Lyapunov stability theory, linear matrix inequalities (LMIs), and the Kronecker product, some sufficient conditions for global synchronization of multiple DTMJMNNs under the event-triggered strategy are derived. Two examples are presented to test the validity of the theoretical analysis results. [ABSTRACT FROM AUTHOR]

Although the cyber-physical system stability is widely studied, scholars focus more on system stability with communication time delay. Therein, grid-connected inverters with the digital control system are regarded as one simplest and typical cyber-physical system. Meanwhile, the switching/sampling frequency of the inverter is always selected as low as possible from an efficiency viewpoint, resulting in unavoidable delay time. This delay time is apt to cause the system instability, which is more prone to severity under weak grid. To this end, this paper provides a minimum switching/sampling frequency for grid-connected inverters. Firstly, the system impedance model with equivalent delay time is constructed, which is based on padé approximate approach. This equivalent delay time consists of three parts, i.e., sampling delay time in cyber/physical level, calculation delay time in cyber level and pulsewidth modulation delay time in physical level, which reflects the cyber-physical interaction impact. Furthermore, the stability forbidden criterion is applied to make the switching/sampling frequency solving process become Hurwitz matrix identification problem through space mappings. Based on these space mappings, an adaptive step search approach is adopted to obtain the minimum switching/sampling frequency. Finally, the proposed approach can well evaluate the system stability under different frequencies through simulation and experiment. [ABSTRACT FROM AUTHOR]

This paper aims to investigate the event-based extended dissipative state estimation problem for memristor-based Markovian neural networks in the presence of hybrid time-varying delays and sensor nonlinearity. To tackle the effect caused by information latching, sudden interference and environmental variation, the Markov jump model is employed to describe the memristor-based neural network. Besides, an event-triggered scheme is introduced to economize the cost of communication. Then some novel conditions are presented, which guarantee that the augmented error system is stochastically stable with an extended dissipative performance. The existence criterion of the desired mode-dependent estimator is also obtained in terms of linear matrix inequalities. Finally, simulation results are provided to show the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

The almost sure finite-time sliding mode control issue is investigated for Markov jump systems. The switching asynchronism between the constructed controller and considered systems is studied. The influence of time-varying delays and disturbances on systems is fully considered, and the sliding mode controller design within a finite time interval is extended to the probability framework. First, the finite time interval is divided into the reaching and the sliding motion phases, and the almost sure finite-time boundedness is analyzed in both phases. Second, the sliding mode controller gain is determined by the provided linear matrix inequality-based criteria. Finally, a numerical example and DC-DC buck converter circuit example verify the effectiveness and less conservativeness of our method. [ABSTRACT FROM AUTHOR]

The continuous-time pipelined (CTP) ADC is a promising emerging high-speed analog-to-digital conversion technique that achieves anti-alias filtering and analog-to-digital conversion in one step. Driving such a converter is easy, thanks to its resistive input impedance. RC time-constant shifts, which will occur in practice due to a change in ambient temperature, degrade the performance of such converters. The aim of this work is to understand this phenomenon, quantify the resulting SNDR degradation, and thereby derive design tradeoffs. The theory is compared with measurements from a three-stage CTP that targets 70dB SNDR in a 100MHz bandwidth while sampling at 800MS/s. [ABSTRACT FROM AUTHOR]

This article shows a focus on the positivity and stability of Cohen-Grossberg-type time-delay memristor neural networks. We start by providing the existence and unique theorem of solutions for time-delay memristor neural networks to the case of unbounded delays. It is clear to find that the discriminate criterion of the existence and uniqueness of solutions about the argumented system with unbounded delays plays an important role in other related unbounded time-delay systems. Leveraging the Lyapunov method along with memristor nonlinearity, sufficient and necessary conditions for positivity and stability of Cohen-Grossberg-type memristor neural networks under unbounded delays are gained. Our proposed criteria don’t need any strictly restrictive conditions. These theoretical results derived here will be helpful to understand the convergence performance of memristor electrical systems. [ABSTRACT FROM AUTHOR]