Description
PHI Learning Spectral Analysis Of Signals by Stoica
This book is an accessible text for students, researchers, and practitioners in the area of Signal Processing. A host of new complements and exercises along with an appendix on model order selection have been included in the new edition to make it a more up-to-date and useful as well as self-contained learning tool for a diversity of students and researchers. The text presents an introduction to spectral analysis. Clear and concise in approach, it covers both classical and modern approaches of spectral analysis. Main topics covered include : 1. Basic concepts autocorrelation ; energy and power spectra. 2. Nonparametric Spectral Analysis : periodogram and correlogram; window-based techniques 3. Rational Spectral Analysis : autoregressive, moving average, and autoregressive moving average methods. 4. Line Spectral Analysis : least squares, Yule??"Walker, and subspace-based methods. 5. Filter-Bank Methods : refined filter banks; the Capon method. 6. Array Signal Processing : beamforming; the Capon method; parametric direction of arrival estimation. 7. Analytical and MATLAB-based computer exercises are included to develop both analytical skills and hands-on experience. Table Of Contents: Preface Notational Conventions Abbreviations Chapter 1Basic Concepts Chapter 2Nonparametric Methods Chapter 3Parametric Methods for Rational Spectra Chapter 4Parametric Methods for Line Spectra Chapter 5Filter-Bank Methods Chapter 6Spatial Methods Appendix ALinear Algebra and Matrix Analysis Tools Appendix BCram??r??"Rao Bound Tools Appendix CModel Order Selection Tools Appendix DAnswers to Selected Exercises Bibliography References Grouped by Subject Index