DESIGN-RLS - RLS Algorithm Guidelines ± Memory parameter ...

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RLS Algorithm: Design guidelines RLS Algorithm: Design guidelines For high SNR (> 30 dB), stationary environments present information reliable : choose λ 1. High SNR, slow non-stationary environment choose λ small & weight present observations more. For low SNR (< 10 dB), present observations unreliable & prior information better: choose λ large & de-emphasize noisy observations.
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Unformatted text preview: RLS Algorithm : Guidelines ± Memory parameter λ provides trade-off between time/frequency resolution. ± For low SNR, initialize inverse recursion with large matrix norm: P[0] = δ I, δ large. ± For high SNR, initialize the inverse recursion with small matrix norm: P[0] = δ I, δ small. ± If environment is highly non-stationary retraining needed....
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