The study of the dynamics of neural networks has greatly attracted the attention of the scientific community because of their promising potential for the tasks of classification, associative memory, and parallel computations, and their ability to solve difficult optimization problems. Many papers [1, 4, 5, 8, 9, 10, 12, 13, 14, 15] have been devoted to discussing the stability of neural network...

In order to enhance the presented synchronization scheme level, this paper deals with the synchronization problem of a class of bidirectional associative memory (BAM) neural networks with delays. Using the drive-response concept, a feedback control law is derived to achieve the state synchronization of two identical BAM neural networks. Moreover, based on the Lyapunov stability method and the H...

This paper is concerned with the delay-distributiondependent stability criteria for bidirectional associative memory (BAM) neural networks with time-varying delays. Based on the Lyapunov-Krasovskii functional and stochastic analysis approach, a delay-probability-distribution-dependent sufficient condition is derived to achieve the globally asymptotically mean square stable of the considered BAM...

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This paper presents two new neural networks, the TASM (Temporal Associative Subject Memory) and the SelfRecurrent network, described as a complex types of recurrent organisms. After a short general definition of recurrent neural networks we introduce the theoretical structure of the new architectures. The paper shows two relevant applications on an medical datasets which show the good classific...

This paper proposes a new arbitrary nonlinear transfer function generator circuit based on pulse-phase modulation. The circuit can generate an arbitrary non-monotone function with an identical circuit con guration. Chaotic signal generators using this function generator are also proposed. Circuit simulation results demonstrate that the new approach achieves high precision transformation. These ...

We derive a new criterion for checking the global stability of periodic oscillation of bidirectional associative memory BAM neural networks with periodic coefficients and distributed delay, and find that the criterion relies on the Lipschitz constants of the signal transmission functions, weights of the neural network, and delay kernels. The proposed model transforms the original interacting ne...

In this lecture I will present some models of neural networks that have been developed in the recent years. The aim is to construct neural networks which work as associative memories. Different attractors of the network will be identified as different internal representations of different objects. At the end of the lecture I will present a comparison among the theoretical results and some of th...

In this paper fuzzy bi-directional associative memory (BAM) neural networks with constant delays are considered. Some sufficient conditions for existence and global exponential stability of unique equilibrium point are established by using fixed point theorem and differential inequality techniques. The results obtained are easily checked to guarantee existence, uniqueness and global exponential...

The Hopfield neural networks and the holographic neural networks are models which were successfully simulated on conventional computers. Starting with these models, an analogous fundamental quantum information processing system is developed in this article. Neuro-quantum interaction can regulate the ”collapse”-readout of quantum computation results. This paper is a comprehensive introduction in...