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ICASSP
2011
IEEE

Sliding window greedy RLS for sparse filters

11 years 3 months ago
Sliding window greedy RLS for sparse filters
We present a sliding window RLS for sparse filters, based on the greedy least squares algorithm. The algorithm adapts a partial QR factorization with pivoting, using a simplified search of the filter support that relies on a neighbor permutation technique. For relatively small window size, the proposed algorithm has a lower complexity than recent exponential window RLS algorithms. Time-varying FIR channel identification simulations show that the proposed algorithm can also give better mean squared coefficient errors.
Alexandru Onose, Bogdan Dumitrescu, Ioan Tabus
Added 20 Aug 2011
Updated 20 Aug 2011
Type Journal
Year 2011
Where ICASSP
Authors Alexandru Onose, Bogdan Dumitrescu, Ioan Tabus
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