This article investigates the problem of robust exponential stability fuzzy switched memristive inertial neural networks (FSMINNs) with time-varying delays on mode-dependent destabilizing impulsive control protocol. The model presented here is treated as a system rather than employing theory differential inclusion and set-value map. To optimize exponentially stable process reduce cost time, hybrid adaptive feedback controllers are simultaneously applied to stabilize FSMINNs. In new model,...

This article investigates the heterogeneous impulsive synchronization for T-S fuzzy probabilistic coupled delayed neural networks (CDNNs) with mode-dependent parameters and piecewise membership functions. To begin with, a novel CDNNs model adjustable coupling strength delays is designed to ensure accuracy of model. Meanwhile, generalized isolated node four types mismatched parameters, named network, first considered extend problem. Then, rules are introduced design model, which implies that...

This paper highlights the memristor bridge-based lowpass filter (LPF) and improved image processing algorithms along with a novel adaptive Gaussian for denoising new pyramid scale invariant feature transform (SIFT). First, kind of LPF based on bridge is designed, whose cut-off frequency other traits are demonstrated to change different time memristance. In light changeable parameter LPF, an SIFT algorithm presented. Finally, experiment results show that peak signalto-noise ratio (PSNR) our...

Matrix operation is easy to be paralleled by hardware, and the memristor network can realize a parallel matrix computing model with in-memory computing. This article proposes matrix-friendly genetic algorithm (MGA), in which population represented evolution of realized operations. Compared performance baseline (GA) on solving maximum value binary function, MGA converge better faster. In addition, more efficient because its parallelism operations, runs 2.5 times faster than GA when using...

This article addresses the problem of dynamic pinning synchronization fuzzy-dependent-switched (Fds) coupled memristive neural networks (CMNNs) with mismatched dimensions on time scales. To begin with, probabilistic coupling delays, scales, dimensions, and function projective rules are considered to design novel CMNNs improve reliability generalization ability model. Then Fds control (DPC) method adopted CMNNs, which can effectively promote information exchange between switching signals...

This article is concerned with the exponential synchronization of coupled memristive neural networks (CMNNs) multiple mismatched parameters and topology-based probability impulsive mechanism (TPIM) on time scales. To begin with, a novel model designed by taking into account three types parameters, including: 1) dimensions; 2) connection weights; 3) time-varying delays. Then, method auxiliary-state variables adopted to deal model, which implies that presented can not only use any isolated...

This article investigates the problem of relaxed exponential stabilization for coupled memristive neural networks (CMNNs) with connection fault and multiple delays via an optimized elastic event-triggered mechanism (OEEM). The two or some nodes can result in other cause iterative faults CMNNs. Therefore, method backup resources is considered to improve fault-tolerant capability survivability In order robustness enhance ability process noise signals, time-varying bounded threshold matrices,...

This paper studies the modeling and exponential stability problems for markovian jumping memristor-based neural networks (MJMNNs) via event-triggered impulsive control scheme (ETICS). The purpose is to design (MNNs) which has parameters hybrid time-vary delays make MNNs more general. Meanwhile, a state estimator introduced estimate system states through vailable output measurements. Furthermore, proposed (ETS), also determined by parameters, used determine whether there an impulse need...

A model to introduce memristive components into the high pass filter (HPF) is highlighted in this paper. Based on Memristor and Memcapacitor, a novel HPF circuit which rarely researched before, provided. In light of first-order RC-HPF Memristor-Capacitor-HPF, new Memristor-Memcapacitor-HPF designed. By studying its transfer function, amplitude-frequency response phase-frequency response, time-varying verified. Finally, simulation results demonstrate our theoretical analysis. Furthermore,...

Active filters based on memristor and memcapacitor (AFMM) including low-pass, high-pass, bandpass, band-stop filter, are studied in this paper. By replacing resistor capacitor with memcapacitor, the novel AFMMs designed. Then transfer function, cut-off frequency, Bode plot demonstrated. Experiment results show that amplitude frequency phase-frequency responses change over time.

In this paper, the finite-time synchronization (FTS) of T-S fuzzy multiplicative stochastic coupled memristive neural networks (CMNNs) with probabilistic delayed impulsive effects is investigated. First, a novel CMNNs model designed, in which mismatched parameters and adjustable coupling strength are considered to ensure accuracy CMNNs. Meanwhile, because noise, different from external input inevitable information transmission. The noise Then, controller introduced enhance robustness system....

This paper investigates the exponential state estimation of discrete-time memristive spiking neural P system (MSNPS). The (SNPS) offers algorithmic support for morphology computation and AI chips, boasting advantages such as high performance efficiency. As a new type information device, memristors have efficient computing characteristics that integrate memory computation, can serve synapses in SNPS. Hence, to harness SNPS synergistically, this presents pioneering MSNPS circuit model, which...

This paper presents global exponential synchronization of drive-response memristor-based recurrent neural networks(MRNNs) with mixed delays. Considering the bounded distributed delays and time-varying as a novel kind delays, MRNNs are proposed. Then, state feedback controller is designed. By using lyapunov functional inequality techniques, criteria on derived. Finally, numerical example simulation results given to illustrate our theoretical results.

A novel memristive elements-based chaotic circuit only containing three elements of memristor, memcapacitor and meminductor is highlighted in this paper. The state equations the are described, dynamical behaviors such as equilibrium set, Lyapunov exponents bifurcation diagram revealed by theoretical analyses numerical simulations. Simulation results demonstrate that sum five negative maximal exponent equal to 0.1773, which verifies typical characteristics limit cycle 1-scroll attractor. most...

This paper presents two circuits: new band-pass filter (BPF), and band-stop (BSF), which are derived from a simple passive RLC series circuit by replacing resistor capacitor with memristor memcapacitor. Compared the traditional filter, these memristive filters show more characteristics like time-varying, flexibility, controllability among others, highlights their potential usage for signal filtering applications. On this basis, division model is designed using time-varying cutoff frequencies...

This paper presents a new kind of electrical circuit which replace traditional resistor, capacitor and inductor with memristor, memcapacitor meminductor. These 3 memory devices constitute RLC circuit. The will show prove the characteristics band-pass band-stop filter including memcapasitor Unlike components, value mem-devices is time-varying, has higher controlability usage. Band-pass further application such as signal processing.

A modified Chua's circuit is implemented meminductor and the improved memristive diode bridge emulator in this paper. The state equations of are described. dynamical behaviors such as equilibrium set, Lyapunov exponents diagram revealed by theoretical analysis numerical simulations. Furthermore, exhibits rich including chaos, hyperchaos, periodic windows, period states, crisis scenarios coexisting attractors. It noted that attractors depend on initial values parameters system. simulation...

This paper is concerned with studying H <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">∞</sub> state estimation of memristor-based recurrent neural networks(MRNNs) mixed delays. The MRNNs addressed comprehensive to cover distributed-delays and time-varying delays in order reflect the reality more closely accurate. delay-dependent design criteria presented under which resulting error system globally asymptotically stable a prescribed performance...

This paper proposes a robust exponential synchronization of inertial memristor-based recurrent neural networks with time-varying delays on impulsive effects. By Using variable transmission, the original second-order system can be transformed into first-order differential system. Impulse is considered when modeling uncertain memristive simultaneously. constructing Lyapunov functional and designing feedback controllers, several sufficient conditions are derived respectively for drive-response...