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Compared to conventional processors, stochastic computing architectures have strong potential to speed up computation time and to reduce power consumption. We present such an architecture, called Bayesian Machine (BM), dedicated to solving Bayesian inference problems. Given a set of noisy signals provided by low-level sensors, a BM estimates the posterior probability distribution of an unknown target...
This paper investigates the problem of network-based fault-tolerant controller design for networked control systems (NCSs) in the presence of random delays and data packet dropouts. A novel actuator fault model which is more general and practical than the conventional actuator fault models is developed. Considering this new fault model, the NCSs are firstly modeled as a Markovian jump system (MJS)...
Delay and security are both highly concerned in the Internet of Things (IoT). In this paper, we set up a secure analytical framework for IoT networks to characterize the network delay performance and secrecy performance. Firstly, stochastic geometry and queueing theory are adopted to model the location of IoT devices and the temporal arrival of packets. Based on this model, a low-complexity secure...
This paper investigates the mean-square stabilizability of a networked discrete-time linear feedback system with multi-step random delay induced by a communication channel. It is assumed that the probability mass function (PMF) of the random delay is known. According to this model, an averaged channel transfer function and the spectral density of the channel uncertainty caused by the delay are obtained...
In this paper, the robust distributed state estimation problem is investigated for a class of discrete-time nonlinear delayed systems over sensor networks with redundant channels. In order to improve the reliability and quality of the communication signal transmission services, redundant channel transmission is utilized to model the communication measurement. The purpose of the addressed problem is...
This paper addresses the problem of the fault detection problem for discrete-time Markovian jump systems under an event-triggered scheme. The event-triggered scheme from the plant to the fault detection filter is utilized to reduce the frequency of transmission. Our attention is focused on the design of a fault detection filter such that the residual system is stochastically stable and satisfies some...
This paper investigates the problem of H∞ state estimation for discrete-time stochastic genetic regulatory networks (GRNs) with switching parameters, time-varying delays, and exogenous disturbances. A new discrete-time stochastic GRN model with switching parameters is proposed by assuming that the sojourn probability of each subsystem of the GRN under consideration is known. By using the stochastic...
The demands of high-speed and power-efficient systems have resulted into the emergence of the approximate computing. Existing approximate circuits as well as stochastic techniques have shown promising advances in improving various figures of merit. However, a through fair comparison of arithmetic units still remains an issue which has not been studied. This paper reviews the prerequisites for a fair...
Behavior of stochastic Petri net can be approximated by difference equation resulting after fluidification. Vásquez et al. have introduced Gaussian noise to reduce approximation error. We suggest a method to reduce the number of additions of noise while keeping errors as small as Vasquez's method.
The H∞ filtering design problem is studied for a class of networked discrete-time nonlinear singular system. Both mixed random delays and packet dropouts in the communication channels are considered. The mixed time-delays consists of the discrete and distributed delays. And the packet dropout phenomenon occurs in a random way. Three mutually independent Bernoulli distributed random variables are utilized...
This paper investigates the stochastic finite-time stability (SFTS) problem for a class of Markovian jump nonlinear systems with time delays. The nonlinear terms are assumed to satisfy the Lipschitz conditions, and the time delays are modelled by mutually independent stochastic variables subject to Bernoulli distributions. The aim of our work is to design a set of linear feedback controllers such...
Aiming at the consensus of leader-follower multi-warhead networked cooperative attack system with stochastic multi-step time-varying delay in the free flight segment of ballistic missile, considering the actual situation, a three-dimensional integrated guidance model of leader-follower multi-warhead cooperative attack system is established. Based on the established model, considering the effect of...
Memristive neurodynamic systems have been deeply developed and analysed in recent years. In this paper, we put forward an improved condition to guarantee the mean-square exponential input-to-state stability (exp-ISS) of stochastic memristive neural networks (MNNs) with time-varying delays. The obtained sufficient condition is novel and less conservative than existing results. Moreover, the condition...
This paper investigates the robustness issue of stochastic nonlinear network control systems (NCSs) with network-induced delays and packet dropouts. Firstly, the controller for the nominal system (without network-induced delays and packet dropouts) is designed to guarantee its globally asymptotic stability. Then, by choosing parameters which satisfy associated conditions, the ultimately globally asymptotic...
Random time delay problem is a key problem in networked control systems (NCSs) and uncertain metrology delay systems. Different from the ordinary delay, the random delay is usually described in time domain. In this paper, a Laplace transform strategy is used to analyze random time delay problem. Firstly, the various Laplace transforms of random variables are discussed; then, based on the output response...
We study the optimal control of fully coupled forward-backward stochastic systems with delay and noisy memory where the dynamics is governed by a controlled Ito-Levy process and the information available to the controller is possibly less than the overall information. Sufficient and necessary maximum principles for the optimal control of such systems are derived using Malliavin calculus techniques...
This paper investigates the problem of mean square exponential stability for uncertain stochastic interval type-2 (IT2) fuzzy neural networks with multiple time-varying delays. First, IT2 fuzzy neural network is introduced, which takes time delays and parameter uncertainties into account. Compared with the existing results, our model is more applicable since time delays and parameter uncertainties...
This paper is to study the stabilizability and stabilization issues of linear dynamical systems based on the delayed and noisy feedback control. For the general linear systems, the necessary conditions and sufficient conditions for mean square and almost sure stabilizability are deduced and the corresponding feedback controls are designed according to the generalized algebraic Riccati equation. It...
In this paper, the problem of controller design for networked control systems with stochastic cyber-attacks is investigated. Firstly, considering the network-induced delay and cyber-attacks, a mathematical controller model for networked control systems is constructed for analysis. Secondly, based on this model, sufficient conditions for the stability of controller design and gain parameters of desired...
This paper is concerned with an optimal control problem of anticipated forward-backward stochastic differential equation with delay. We obtain an explicit representation of optimal control for delayed problem first, and then use it to solve a delayed cash management problem with recursive utility. The explicit optimal control strategy of the investor is given and some numerical simulations are used...
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