Wojbor A. Woyczynski

A First Course in Statistics for Signal Analysis (eBook, PDF)

• Format: PDF

Produktbeschreibung

This essentially self-contained, deliberately compact, and user-friendly textbook is designed for a first, one-semester course in statistical signal analysis for a broad audience of students in engineering and the physical sciences. The emphasis throughout is on fundamental concepts and relationships in the statistical theory of stationary random signals, explained in a concise, yet fairly rigorous presentation.

Developed by the author over the course of several years of classroom use, A First Course in Statistics for Signal Analysis may be used by junior/senior undergraduates or graduate students in electrical, systems, computer, and biomedical engineering, as well as the physical sciences. The work is also an excellent resource of educational and training materials for scientists working in research laboratories.

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Produktdetails

• Verlag: Birkhäuser Boston
• Seitenzahl: 208
• Erscheinungstermin: 26. Mai 2007
• Englisch
• ISBN-13: 9780817645168
• Artikelnr.: 38238328

Autorenporträt

Wojbor A. Woyczy¿ski is a Professor in the Department of Statistics and the Director of the Center for Stochastic and Chaotic Processes in Science and Technology at Case Western Reserve University. His research interests include probability theory, Lévy stochastic processes, random fields and their statistics, nonlinear, stochastic and fractional evolution equations, harmonic and functional analysis, random graphs, statistical physics and hydrodynamics, chaotic dynamics, applications to chemistry, physics, operations research, financial mathematics, medicine, oceanography, and atmospheric physics. 

Inhaltsangabe

Description of Signals.- Spectral Representation of Deterministic Signals: Fourier Series and Transforms.- Uncertainty Principle and Wavelet Transforms.- Random Variables and Random Vectors.- Stationary Signals.- Power Spectra of Random Signals.- Transmission of Stationary Signals through Linear Systems.- Optimization of Signal-to-Noise Ratio in Linear Systems.- Gaussian Signals, Covariance Matrices, and Sample Path Properties.- Spectral Representation of Discrete-Time Signals and Their Computer Simulations.- Prediction Theory for Stationary Random Signals.- Solutions to Selected Problems and Exercises.