ON SYSTEM IDENTIFICATION WITH AND WITHOUT CERTAINTY
- 17 April 1978
- journal article
- research article
- Published by Taylor & Francis in Journal of Cybernetics
- Vol. 8 (1) , 31-50
- https://doi.org/10.1080/01969727808927569
Abstract
Information-theoretic concepts are utilized to develop a procedure for identifying a parameter of a stochastic linear discrete time dynamic scalar system based on noisy linear measurements of the system's state. After various simplifying approximations, the derived error entropy identification algorithm reduces to an on-line adaptive identification algorithm that is similar in many respects to well-established identification techniques. Conditions under which the developed on-line adaptive algorithm identifies the system with certainty are presented. Using an error entropy estimation lower bound, which is independent of any estimation procedure, conditions for which identification cannot be made with certainty are also presented. Examples involving non-Gaussian statistics are used to illustrate the efficiency of the error entropy adaptive identification algorithm as well as to compare it with several other identification procedures.Keywords
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