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Analog Computing for Real-Time Solution of Time-Varying Linear Equations

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Date

2004

Authors

Jiang, Danchi

Journal Title

Journal ISSN

Volume Title

Publisher

Institute of Electrical and Electronics Engineers (IEEE Inc)

Abstract

An implicit recurrent neural network model (IRNN) is proposed in this paper for solving on-line time-varying linear equations. Such a neural network can be implemented as analog circuits or VLSI. Excellent convergent properties have been revealed by careful theoretical analysis. In the specific case where the linear equation is obtained from a time-varying Sylvester equation, the proposed IRNN model coincides with some existing recurrent neural networks reported in recent literature, where simulation examples have been reported to demonstrate the effectiveness and efficiency.

Description

Keywords

Keywords: Computer simulation; Iterative methods; Linear equations; Optimization; Real time systems; Recurrent neural networks; Time varying systems; VLSI circuits; Implicit recurrent neural network (IRNN) model; Real-time computation; Sylvester equations; Time-var Implicit recurrent neural network; Real-time computation; Sylvester equation; Time-varying linear equations

Citation

URI

http://hdl.handle.net/1885/80850

Collections

ANU Research Publications

Source

2004 International Conference on Communications, Circuits and Systems

Type

Conference paper

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