Abstract

Recurrent neural networks have received much attention due to their nonlinear dynamic behavior. One such type of dynamic behavior is that of setting a fixed stable state. This paper shows a counterexample to the claim of A.N. Michel et al. (IEEE Control Systems Magazine, vol. 15, pp. 52-65, Jun. 1995), that "sparse constraints on the interconnecting structure for a given neural network are usually expressed as constraints which require that pre-determined elements of T [a real n×n matrix acting on a real n-vector valued function] be zero", for the synthesis of sparsely interconnected recurrent neural networks.

Meeting Name

2002 International Joint Conference on Neural Networks, 2002. IJCNN '02

Department(s)

Electrical and Computer Engineering

Keywords and Phrases

Constraint Theory; Fixed Stable State; Network Synthesis; Neural Net Interconnecting Structure; Nonlinear Dynamic Behavior; Pre-Determined Matrix Elements; Recurrent Neural Nets; Recurrent Neural Network Synthesis; Sparse Constraints; Sparse Matrices; Sparsely Interconnected Networks; Stability

Document Type

Article - Conference proceedings

Document Version

Final Version

File Type

text

Language(s)

English

Rights

© 2002 Institute of Electrical and Electronics Engineers (IEEE), All rights reserved.

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