Fast algorithms for lpdeconvolution
Rao Yarlagadda, J. Bee Bednar, Tess Watt · IEEE Transactions on Acoustics Speech and Signal Processing · 1985
This paper discusses two algorithms forl_{p}, 1 \leq p \leq 2, deconvolution. One, iterative reweighted least squares (IRLS), is discussed with an eye toward improving its computational efficiency, while the other, residual steepest descent (RSD), is considered in an attempt to improve its convergence properties. In the first case, fast Fourier transforms are used to reduce the number of computations. In the second, a new rescaling procedure which enhances RSD convergence is introduced. The lack of stability of l1, filters, and its implications are discussed. Simple examples are used to illustrate pertinent concepts.