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1

The Stochastic Loss of Spikes in Spiking Neural P Systems : Design and Implementation of Reliable Arithmetic Circuits

Xu Z., Cavaliere M., An P., Vrudhula S., Cao Y

Fundamenta Informaticae

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2014

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Vol. 134, nr 1/2

183--200

EN

Spiking neural P systems (in short, SN P systems) have been introduced as computing devices inspired by the structure and functioning of neural cells. The presence of unreliable components in SN P systems can be considered in many different aspects. In this paper we focus on two types of unreliability: the stochastic delays of the spiking rules and the stochastic loss of spikes. We propose the implementation of elementary SN P systems with DRAM-based CMOS circuits that are able to cope with these two forms of unreliability in an efficient way. The constructed bio-inspired circuits can be used to encode basic arithmetic modules.

2

LMI optimization problem of delay-dependent robust stability criteria for stochastic systems with polytopic and linear fractional uncertainties

Balasubramaniam P., Lakshmanan S., Rakkiyappan R.

International Journal of Applied Mathematics and Computer Science

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2012

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Vol. 22, no. 2

339-351

EN

This paper studies an LMI optimization problem of delay-dependent robust stability criteria for stochastic systems with polytopic and linear fractional uncertainties. The delay is assumed to be time-varying and belong to a given interval, which means that lower and upper bounds of this interval time-varying delay are available. The uncertainty under consideration includes polytopic-type uncertainty and linear fractional norm-bounded uncertainty. Based on the new Lyapunov-Krasovskii functional, some inequality techniques and stochastic stability theory, delay-dependent stability criteria are obtained in terms of Linear Matrix Inequalities (LMIs). Moreover, the derivative of time delays is allowed to take any value. Finally, four numerical examples are given to illustrate the effectiveness of the proposed method and to show an improvement over some results found in the literature.

3

Stochastically Excited Nonlinear Systems

Wagner U.

Machine Dynamics Problems

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2007

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Vol. 31, No. 2

140-154

EN

The solution of high dimensional probability density functions of nonlinear mechanical systems by solving the corresponding Fokker-Planck equation constitutes still a serious problem. The paper gives an overview of a method proposed by the author which was applied successfully for a wide range of nonlinear systems. This method is illustrated by an example from vehicle dynamics. Additionally nonlinear systems are considered which contain multiple stable stationary solutions in the deterministic case. These systems are excited by an additional white noise resulting in interesting shapes of probability density functions which are calculated by solving Fokker-Planck equations. Ali results are compared by corresponding Monte Carlo simulations.

4

On some tasks of stochastic systems optimal estimations of functional-differential equations.

Miniuk S., Boiko V., Naumovich L.

Systems Science

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2002

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Vol. 28, nr 1

25-44

EN

The algorithms of optimal estimation problem solutions for systems of linear functional-differential equations are obtained for the case of initial information of the object of observation being present and in its absence.

5

Fault diagnosis and fault tolerant control of linear stochastic systems with unknown inputs.

Lee J.H., Lyou J.

Systems Science

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2001

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Vol. 27, nr 3

59-76

EN

This paper presents an integrated robust fault detection and isolation (FDI) and fault tolerant control (FTC) scheme for a fault in actuators or sensors of linear stochastic systems subjected to unknown inputs (disturbances). As usual in this kind of works, it is assumed that single fault occurs at a time and the fault treated is of random bias type. The FDI module is constructed using banks of robust two-stage Kalman filters, which simultaneously estimate the state and the fault bias, and generate residual sets decoupled from unknown disturbances. All elements of residual sets are evaluated by using a hypothesis statistical test, and the fault is declared according to the prepared decision logic. The FTC module is activated based on the fault indicator, and additive compensation signal is computed using the fault bias estimate and combined to the nominal control law for compensating the fault's effect on the system. Simulation results for the simplified longitudinal flight control system with parameter variations, process and measurement noises demonstrate the effectiveness of the approach proposed.

6

Parametric minimization of influence of stochastic didtribution in linear systems

Banek T.

Archives of Control Sciences

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1998

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Vol. 7, no. 1/2

99-104

EN

A structure optimization problem in linear systems is considered. It is shown that parametric minimization (in the mean square sense) of influence of stochastic disturbation can be reduced to some nonlinear programming problem. Sufficient condition for equivalence of these problems and existence of their solutions are given. It is also shown how to apply the results to controlled systems.