Ultimate Objectives and Prior Knowledge in System Identification

Abstract This paper examines some aspects of the roles of ultimate objectives and prior knowledge in system identification. It is shown that often an ultimate objective can be achieved without unique parameter or structure determination. New results based on this approach in adaptive prediction will be presented. Recent related results in adaptive control will also be examined to illustrate the role of identifciation when minimum variance control is the ultimate objective.

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