A global gradient descent algorithm for hierarchical FIR adaptive filters
2002 14th International Conference on Digital Signal Processing Proceedings. DSP 2002 (Cat. No.02TH8628) - Tập 2 - Trang 1285-1288 vol.2
Tóm tắt
We present an extension of the recently introduced hierarchical least mean square (HLMS) algorithm. The original algorithm suffers from two major drawbacks, namely the incapability to converge for every unknown channel and the dramatic deterioration of its performance as the number of levels increases significantly. To be able to cope with these, a novel global gradient descent algorithm is proposed. This algorithm converges for every class of unknown filters and it exhibits faster convergence than HLMS in any case.
Từ khóa
#Finite impulse response filter #Adaptive filters #Signal processing algorithms #Convergence #Adaptive signal processing #Eigenvalues and eigenfunctions #Biomedical signal processing #Computational complexity #Least squares approximation #Neural networksTài liệu tham khảo
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