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- W1836739929 abstract "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." @default.
- W1836739929 created "2016-06-24" @default.
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- W1836739929 date "2002-11-22" @default.
- W1836739929 modified "2023-09-26" @default.
- W1836739929 title "An executable and asymptotically optimal adaptive RLS algorithm" @default.
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- W1836739929 doi "https://doi.org/10.1109/sice.1997.625051" @default.
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