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- W2378622905 abstract "Non-Gaussian and non-stationary random signal processing is an interesting and important topic in the field of signal processing,and it has important academic significance and practical value. Since the conventional algorithms based on the recursive least square (RLS) algorithm degenerate severely under the α-stable distribution noise conditions,an autoregressive (AR) model with time-varying coefficients is used to track the non-stationary characteristics of the signal,and its coefficients are estimated with the least p-norm algorithm (LPN). The experimental results show that the LPN algorithm is applicable not only under Gauss noise but also under the conditions of α-stable distribution noise. Furthermore,the LPN algorithm has better flexibility compared with RLS algorithm which is applicable only under Gauss noise." @default.
- W2378622905 created "2016-06-24" @default.
- W2378622905 creator A5016034793 @default.
- W2378622905 date "2010-01-01" @default.
- W2378622905 modified "2023-09-23" @default.
- W2378622905 title "Parameter estimation of time-varying autoregressive model under α-stable distributed noise conditions" @default.
- W2378622905 hasPublicationYear "2010" @default.
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