An executable and asymptotically optimal adaptive RLS algorithm
説明
A setting method for the forgetting factor in recursive least squares (RLS) algorithms is presented. In a general adaptive setting method, to obtain the optimal value of the forgetting factor, the cost function constructed with the mean squared prediction errors is differentiated and the derivative that is set to zero is solved numerically. The problem of this method is that just one of local minimums is obtained unless the cost function is confirmed as unimodal. The main object of this contribution is to show the unimodality of the cost function of the RLS algorithm.
収録刊行物
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- Proceedings of the 36th SICE Annual Conference. International Session Papers
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Proceedings of the 36th SICE Annual Conference. International Session Papers 1317-1320, 2002-11-22
Soc. Instrum. & Control Eng