Global dissipativity analysis for delayed quaternion-valued neural networks.
Journal:
Neural networks : the official journal of the International Neural Network Society
Published Date:
Feb 4, 2017
Abstract
The problem of global dissipativity analysis for quaternion-valued neural networks (QVNNs) with time-varying delays is firstly investigated in this paper. The QVNN is studied as a single entirety without any decomposition. Several algebraic conditions ensuring the global dissipativity and globally exponential dissipativity for QVNNs are derived by employing Lyapunov theory and some analytic techniques. Furthermore, the positive invariant sets, globally attractive sets and globally exponentially attractive sets are figured out as well. Finally, the effectiveness is notarized by deducing two simulation examples.
