A novel technique for tracking time-varying minimum and its applications

Author

Zhao, Y. ; Swamy, M.N.S.

Author_Institution

Dept. of Electr. & Comput. Eng., Concordia Univ., Montreal, Que., Canada

Volume

2

fYear

1998

fDate

24-28 May 1998

Firstpage

910

Abstract

A technique for tracking the time-varying minimum of a time-dependent function is proposed. It ensures the tracking process converge exponentially. It also enables the tracking to move from the minimum at one instant of time to the minimum at the next instant of time, without any error. Examples are given to show that this technique is effective for tracking the time-varying minimum. Application of this technique to on-line continuous system identification, on-line neural network learning, etc. gives rise to improved results

Keywords

Newton method; convergence of numerical methods; feedforward neural nets; identification; learning (artificial intelligence); optimisation; time-varying systems; tracking; Newton technique; exponential convergence rate; feed forward neural network; on-line continuous system identification; on-line neural network learning; optimization; time-dependent function; time-varying minimum tracking; Analog circuits; Application software; Continuous time systems; Control systems; Counting circuits; Electronic circuits; Equations; Neural networks; Signal processing; System identification;

fLanguage

English

Publisher

ieee

Conference_Titel

Electrical and Computer Engineering, 1998. IEEE Canadian Conference on

Conference_Location

Waterloo, Ont.

ISSN

0840-7789

Print_ISBN

0-7803-4314-X

Type

conf

DOI

10.1109/CCECE.1998.685646

Filename

685646