This paper deals with the problem of stability of neural networks with leakage, discrete and distributed delays. A new Lyapunov functional which contains some new double integral terms are introduced. By using appropriate model transformation that shifts the considered systems into the neutral-type time-delay system, and by making use of some inequality techniques, delay-dependent criteria are ...

In this paper, by employing a new Lyapunov functional and an elementary inequality analysis technique, some sufficient conditions are derived to ensure the existence and uniqueness of periodic oscillatory solution for fuzzy bi-directional memory (BAM) neural networks with time-varying delays, and all other solutions of the fuzzy BAM neural networks converge the uniqueness periodic solution. The...

This article is concerned with the in-domain stabilization of a class block diagonal infinite-dimensional systems in presence an uncertain and time-varying delay distributed control input. Two actuation schemes are considered. The first one assumes input that fully over domain. second finite-dimensional, acting domain via bounded operator. In both cases, design strategy consists predictor feedb...

Precise timing of synaptic inputs is a fundamental principle of neural circuit processing. The temporal precision of postsynaptic input integration is known to vary with the computational requirements of a circuit, yet how the timing of action potentials is tuned presynaptically to match these processing demands is not well understood. In particular, action potential timing is shaped by the axo...

In this paper, the robust exponential stability problem of discrete-time uncertain stochastic neural networks with timevarying delays is investigated. By introducing a new augmented Lyapunov function, some delay-dependent stable results are obtained in terms of linear matrix inequality (LMI) technique. Compared with some existing results in the literature, the conservatism of the new criteria i...

A central problem in cortical processing including sensory binding and attentional gating is how neurons can synchronize their responses with zero or near-zero time lag. For a spontaneously firing neuron, an input from another neuron can delay or advance the next spike by different amounts depending upon the timing of the input relative to the previous spike. This information constitutes the ph...

In this work we describe a new method that adjusts time-delays and the widths of time-windows in artificial neural networks automatically. The input of the units are weighted by a gaussian input-window over time which allows the learning rules for the delays and widths to be derived in the same way as it is used for the weights. Our results on a phoneme classification task compare well with res...

Abstract: A flexible controller for optimal control of linear time-varying stochastic systems with multiple time delays is developed. The plants to be controlled are represented using a multi-input multi-output controlled autoregressive moving average model. The delays are described using a diagonal matrix. Input and output filters in the form of linear time-varying moving average operators are...

Time delays are ubiquitous in the nervous system. Empirical "ndings suggest that time delays are adapted when considering the synchronous activity of neurons. We introduce a framework for studying the dynamics of self-organized delay adaptation in systems which optimize coincidence of inputs. The framework comprises two families of delay adaptation mechanisms, delay shift and delay selection. F...