Signal extrapolation in noisy data with wavelet representation

Li-Chien Lin; C.-C. Jay Kuo

doi:10.1117/12.160431

1 November 1993 Signal extrapolation in noisy data with wavelet representation

Li-Chien Lin, C.-C. Jay Kuo

Proceedings Volume 2027, Advanced Signal Processing Algorithms, Architectures, and Implementations IV; (1993) https://doi.org/10.1117/12.160431
Event: SPIE's 1993 International Symposium on Optics, Imaging, and Instrumentation, 1993, San Diego, CA, United States

Abstract

A new approach for signal extrapolation based on wavelet representation known as scale-time limited extrapolation and a denoising process is investigated in this research. We first examine a new signal modeling technique using wavelets and the corresponding scale-time limited signal extrapolation algorithm. Then, the sensitivity of the algorithm to noise is discussed, and a denoising algorithm based on the time-localization property of the wavelet transform is proposed. By integrating the denoising process and the iterative scale-time limited extrapolation algorithm, we obtain a very robust signal extrapolation algorithm for noisy data. A simulation result of signal extrapolation from noisy observed data is presented to illustrate the performance of the proposed robust signal extrapolation algorithm.

Citation Download Citation

Li-Chien Lin and C.-C. Jay Kuo "Signal extrapolation in noisy data with wavelet representation", Proc. SPIE 2027, Advanced Signal Processing Algorithms, Architectures, and Implementations IV, (1 November 1993); https://doi.org/10.1117/12.160431

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