Denoising radiocommunications signals by using iterative wavelet shrinkage | Zendy

Baxter Paul D. | Zendy; Upton Graham J. G. | Zendy

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Denoising radiocommunications signals by using iterative wavelet shrinkage

Author(s) -

Baxter Paul D.,

Upton Graham J. G.

Publication year - 2002

Publication title -

journal of the royal statistical society: series c (applied statistics)

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 1.205

H-Index - 72

eISSN - 1467-9876

pISSN - 0035-9254

DOI - 10.1111/1467-9876.00276

Subject(s) - wavelet , computer science , second generation wavelet transform , noise reduction , wavelet packet decomposition , noise (video) , pattern recognition (psychology) , wavelet transform , artificial intelligence , context (archaeology) , stationary wavelet transform , contrast (vision) , discrete wavelet transform , signal (programming language) , lifting scheme , signal processing , speech recognition , algorithm , digital signal processing , image (mathematics) , geology , paleontology , computer hardware , programming language

Summary. Radiocommunications signals pose particular problems in the context of statistical signal processing. This is because short‐term fluctuations (noise) are a consequence of atmospheric effects whose characteristics vary in both the short and the longer term. We contrast traditional time domain and frequency domain filters with wavelet methods. We also propose an iterative wavelet procedure which appears to provide benefits over existing wavelet methods.

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