Anti-periodic behavior for quaternion-valued delayed cellular neural networks

Neural Networks for Quaternion-valued Function Approximation

In the paper a new structure of Multi-Layer Perceptron, able to deal with quaternion-valued signal, is proposed. A learning algorithm for the proposed Quaternion MLP (QMLP) is also derived. Such a neural network allows to interpolate functions of quaternion variable with a smaller number of connections with respect to the corresponding real valued MLP. INTRODUCTION In the last few years, neural...

Scaled Conjugate Gradient Learning for Quaternion-Valued Neural Networks

Quaternion Valued Neural Networks and Nonlinear Adaptive Filters

A class of locally analytic transcendental functions suitable for nonlinear adaptive filtering and neural network filtering is proposed. Since the stringent standard analyticity conditions prevent full exploitation of nonlinear quaternionic models, we make use of local analyticity conditions to provide a framework for a generic extension of nonlinear learning algorithms from the real and comple...

Dynamics of Periodic Delayed Planar Neural Networks

Abstract: This paper formulates and studies a model of periodic delayed planar systems. The model can well describe many practical architecture of delayed neural networks, which is generation of some existing neural such as delayed cellular networks(DCN) and periodic delayed neural networks(PDNNS). The existence and global exponential stability of PDPNN’s periodic solutions are investigated, wi...

Periodic Solution and Global Exponential Stability for Shunting Inhibitory Delayed Cellular Neural Networks

For a class of neural system with time-varying perturbations in the time-delayed state, this article studies the periodic solution and global robust exponential stability. New criteria concerning the existence of the periodic solution and global robust exponential stability are obtained by employing Young’s inequality, Lyapunov functional, and some analysis techniques. At the same time, the glo...