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Variable p norm constrained LMS algorithm based on gradient of root relative deviation.pdf
[article]
2016
arXiv
pre-print
A new Lp-norm constraint least mean square (Lp-LMS) algorithm with new strategy of varying p is presented, which is applied to system identification in this letter. The parameter p is iteratively adjusted by the gradient method applied to the root relative deviation of the estimated weight vector. Numerical simulations show that this new algorithm achieves lower steady-state error as well as equally fast convergence compared with the traditional Lp-LMS and LMS algorithms in the application
arXiv:1603.09022v1
fatcat:wqq3gnnukvabzgfttnxnuot5ju