Title :
Discrete-Time Recurrent Neural Networks With Complex-Valued Linear Threshold Neurons
Author :
Zhou, Wei ; Zurada, Jacek M.
Author_Institution :
Comput. Intell. Lab., Univ. of Electron. Sci. & Technol. of China, Chengdu, China
Abstract :
This brief discusses a class of discrete-time recurrent neural networks with complex-valued linear threshold neurons. It addresses the boundedness, global attractivity, and complete stability of such networks. Some conditions for those properties are also derived. Examples and simulation results are used to illustrate the theory.
Keywords :
complex networks; electronic engineering computing; network synthesis; recurrent neural nets; stability; boundedness; complex-valued linear threshold neurons; discrete-time recurrent neural networks; global attractivity; network stability; Complex-valued neural networks (NNs); discrete-time recurrent neural networks (RNNs); linear threshold (LT);
Journal_Title :
Circuits and Systems II: Express Briefs, IEEE Transactions on
DOI :
10.1109/TCSII.2009.2025625
