Mathematical transformations and estimation methods in signal processing

Author: Xu Boxun
Publisher:
Publish Date: 2004-07-01
Features: This book introduces commonly used mathematical transformations and estimation methods in signal processing. In terms of writing style, it avoids complex mathematical proofs and strives to be accessible and easy to understand. The book incorporates the author's practical experience from years of research in signal processing. Regarding mathematical transformations, it covers orthogonal transformations such as Fourier transform, Z-transform, Laplace transform, wavelet transform, Hilbert transform, Walsh transform, and number-theoretic transform, as well as a special type of nonlinear transformation—the homomorphic transform. As for estimation methods, it includes minimum linear variance estimation, maximum likelihood estimation, least squares estimation, and modern spectral estimation methods. This book can serve as a reference for undergraduate and graduate students in applied mathematics, computational mathematics, geophysical data processing, and communication technology, as well as for relevant engineering professionals.