Abstract
A variant of Hopfield neural network, called the modified Hopfield network, is formulated in this study. This class of networks consists of parallel recurrent networks which have variable dimensions that can be changed to fit the problem under consideration. It has a structure to implement an inverse transformation that is essential for embedding optimal control gain sequences. Equilibrium solutions of this network are discussed. The robustness of this network and the classical Hopfield network are carried out in the frequency domain using describing functions
Recommended Citation
J. Shen and S. N. Balakrishnan, "Frequency Domain Robustness Analysis of Hopfield and Modified Hopfield Neural Networks," Proceedings of the 1999 American Control Conference, 1999, Institute of Electrical and Electronics Engineers (IEEE), Jan 1999.
The definitive version is available at https://doi.org/10.1109/ACC.1999.786345
Meeting Name
1999 American Control Conference, 1999
Department(s)
Mechanical and Aerospace Engineering
Keywords and Phrases
Hopfield Neural Nets; Hopfield Neural Networks; Circuit Stability; Frequency Domain Analysis; Frequency-Domain Analysis; Inverse Problems; Inverse Transformation; Optimal Control; Recurrent Networks; Robustness; Stability; Transforms
Document Type
Article - Conference proceedings
Document Version
Final Version
File Type
text
Language(s)
English
Rights
© 1999 Institute of Electrical and Electronics Engineers (IEEE), All rights reserved.
Publication Date
01 Jan 1999
