Modern Signal Processing

Häftad, Engelska, 2022

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The book systematically introduces theories of frequently-used modern signal processing methods and technologies, and focuses discussions on stochastic signal, parameter estimation, modern spectral estimation, adaptive filter, high-order signal analysis and non-linear transformation in time-domain signal analysis. With abundant exercises, the book is an essential reference for graduate students in electrical engineering and information science.

Produktinformation

Utgivningsdatum2022-12-05
Mått170 x 240 x undefined mm
Vikt985 g
FormatHäftad
SpråkEngelska
SerieDe Gruyter STEM
Antal sidor601
FörlagDe Gruyter
ISBN9783110475555
ÖversättareWang, Xiyuan, Chang, Dongxia, Zhang, Ling, Zhang, Daoming

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Table of content:Chapter 1: Stochastic signal - correlation function, covariance function, power spectral density, signal identification, signal transformation, linear system with random input signalChapter 2: Parameter estimation - estimators, Fisher information and Cramer-Rao inequality, Bayes estimation, maximum likelihood estimation, least-square estimationChapter 3: Modern spectral estimation - discrete stochastic process, non-parametric spectral analysis, stationary ARMA process and spectral density, ARMA spectral estimation, ARMA identification, maximum entropy spectrum estimation, Pisarenko harmonic decomposition, extended Prony method, MUSIC, ESPRITChapter 4: Adaptive filter - Wiener filter for continuous time, Optimization, Kalman filter, LMS adaptive algorithm and filter, RLS adaptive algorithm, operator theory for adaptive filter, adaptive line enhancer, trap filter, generalized sidelobe canceller, blind adaptive multi-user detectionChapter 5: High-order statistical analysis - matrix and cumulative domain, high-order spectral, non-Gussian signal and linear system, FIR system identification, ARMA model identification, harmonic retrieval in color noise, time delay estimation, double spectral and application in signal classificationChapter 6: Linear transformation in time-domain signal analysis - local transformation, analytic signal, Fourier transformation, Gabor transformation, wavelet transformation and framework theory, multi-resolution analysis, quadrature filter, bi-quadrature filter, Gabor atoms and applications in radar signal detectionChapter 7: Nonlinear transformation in time-domain signal analysis - time domain distribution, Wigner-Ville distribution, fuzzy function, Cohen qusi-time domain distribution, evaluation and optimization of time domain distribution, time domain distribution for FM signal