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


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





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

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