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- Author: Steven M. Kay
- Language: English
- ISBN/ASIN: 130724106
- ISBN13: 9780130724106
- Upload date: 16-12-2016, 20:56
- Category: Engineering

Although by training I am an electrical engineer, my PhD dissertation is in bio-stats (more specifically multiple testing). Therefore, I have been forced to do some thinking about the issues of detection and estimation both from performance in engineering systems and from scientific inference point of view. By now, I have done statistical work in bunch of different fields -wireless comm, speech recognition, machine learning, bioinformatics, and biostatistics. While I learned dectection and estimation for the first time, which was 5-6 years ago, I did not use Kay's book, but when couple of years ago I was beating my head over certain Frequentist/Bayesian differences, I accidentally ran into this book that lies in my Prof's collection.

Kay is plain good. He seem to have an amazingly clarity about these issues. His treatment is sometimes too direct and simple that you feel there must be some catch. But now I am increasingly getting convinced that there is none. This book surmounts much confusion that is ingrained to statistical literature of this level and scope. I have read a lot of references but I don't know many that make Neyman-Pearson Lemma or Cramer-Rao bound so clear and straightforward. Summaries at the beginning of each chapter (yes beginning) are right-on-the-button especially for those who have been in the field for a while and still occasionally need coordinates. The book is perfect as a textbook in a comprehensive graduate course on estimation-detection or as a handy reference.

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Fundamentals Of Statistical Signal Processing (2 Volumes) Download via usenet
Signal Detection and Estimation [With CDROM] (Artech House Radar Library) Event-Based Control and Signal Processing (Embedded Systems) Statistical Theory: A Concise Introduction Statistical Inference Based on Divergence Measures (Statistics: A Series of Textbooks and Monographs) Probability, Random Processes, and Statistical Analysis: Applications to Communications, Signal Processing, Queueing Theory and Mathematical Finance Nonlinear Signal Processing: A Statistical Approach (Wiley-Interscience) Mathematical Statistics - Springer Texts in Statistics Large-Scale Inference: Empirical Bayes Methods for Estimation, Testing, and Prediction (Institute of Mathematical Statistics Monographs) Introductory Statistical Inference with the Likelihood Function Introduction to Statistical Pattern Recognition, Second Edition Introduction to Bayesian Statistics, 2nd Edition Essential Statistical Inference: Theory and Methods Constrained Statistical Inference: Order, Inequality, and Shape Constraints Bayesian Bounds for Parameter Estimation and Nonlinear Filtering/Tracking An Introduction to Generalized Linear Models, Third Edition (Chapman & Hall/CRC Texts in Statistical Science) An Elementary Introduction to Statistical Learning Theory Statistical Methods for Financial Engineering (Chapman & Hall/CRC Financial Mathematics) Fourier Transform - Signal Processing Detection Estimation and Modulation Theory, Part I Statistical Signal Processing: Modelling and Estimation Signals, Systems and Inference Signal Processing for Cognitive Radios Principles of Signal Detection and Parameter Estimation Introduction to Direction-Of-Arrival Estimation (Artech House Signal Processing Library)

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