Multistability of recurrent neural networks with time-varying delays and the piecewise linear activation function. Academic Article

abstract

• In this brief, stability of multiple equilibria of recurrent neural networks with time-varying delays and the piecewise linear activation function is studied. A sufficient condition is obtained to ensure that n-neuron recurrent neural networks can have (4k - 1)(n) equilibrium points and (2k)(n) of them are locally exponentially stable. This condition improves and extends the existing stability results in the literature. Simulation results are also discussed in one illustrative example.

authors

• Huang, Tingwen

published proceedings

• IEEE Trans Neural Netw

author list (cited authors)

• Zeng, Z., Huang, T., & Zheng, W. X.

citation count

• 181

complete list of authors

• Zeng, Zhigang||Huang, Tingwen||Zheng, Wei Xing

publication date

• August 2010

publisher

• Institute of Electrical and Electronics Engineers (IEEE)  Publisher

published in

• IEEE Transactions on Neural Networks and Learning Systems  Journal

keywords

• Algorithms
• Animals
• Artificial Intelligence
• Brain
• Humans
• Linear Models
• Mathematical Concepts
• Memory
• Nerve Net
• Neural Networks, Computer
• Neurons
• Reaction Time
• Time Factors

Digital Object Identifier (DOI)

• 10.1109/TNN.2010.2054106

start page

• 1371

end page

• 1377

volume

• 21

issue

• 8

URL

• http://dx.doi.org/10.1109/tnn.2010.2054106