Most Complete Solution manual for Fundamentals of Statistical Signal Processing :Estimation Theory by Steven M Kay Volume One (ch1-14) DOWNLOAD NOW
Most Complete Solution manual for Fundamentals of Statistical Signal Processing :Estimation Theory by Steven M Kay Volume One (ch1-15) DOWNLOAD NOW
Signal Processing An International Journal (SPIJ Volume (4) : Issue (5)
Fundamentals of Electric Circuits Alexander 4th Edition Solutions Manual
Fundamentals of Financial Management Brigham 12th Edition Solutions Manual
Fundamentals of Financial Management Brigham 12th Edition Test Bank
Fundamentals of Heat and Mass Transfer Incropera 6th Edition Solutions Manual
Fundamentals of Corporate Finance Ross 9th Edition Test Bank
Fundamentals of Corporate Finance Ross 9th Edition Solutions Manual
Fundamentals of Anatomy & Physiology Martini 8th Edition Test Bank
The most comprehensive overview of signal detection available.
This is a thorough, up-to-date introduction to optimizing detection algorithms for implementation on digital computers. It focuses extensively on real-world signal processing applications, including state-of-the-art speech and communications technology as well as traditional sonar/radar systems.
Start with a quick review of the fundamental issues associated with mathematical detection, as well as the most important probability density functions and their properties. Next, review Gaussian, Chi-Squared, F, Rayleigh, and Rician PDFs, quadratic forms of Gaussian random variables, asymptotic Gaussian PDFs, and Monte Carlo Performance Evaluations.
Three chapters introduce the basics of detection based on simple hypothesis testing, including the Neyman-Pearson Theorem, handling irrelevant data, Bayes Risk, multiple hypothesis testing, and both deterministic and random signals.
The author then presents exceptionally detailed coverage of composite hypothesis testing to accommodate unknown signal and noise parameters. These chapters will be especially useful for those building detectors that must work with real, physical data. Other topics covered include:
The book makes extensive use of MATLAB, and program listings are included wherever appropriate. Designed for practicing electrical engineers, researchers, and advanced students, it is an ideal complement to Steven M. Kay's Fundamentals of Statistical Signal Processing, Vol. 1: Estimation Theory (Prentice Hall PTR, 1993, ISBN: 0-13-345711-7).
Use coupon below to get discount at eCampus.com!
$3 off textbook orders over $75
$4 off textbook orders over $90
$5 off textbook orders over $100
Copy the coupon code before clicking the button!
|Amazon US||Paperback||$75.00 - $117.00|
This book is Volume I of the series DSP for MATLAB™ and LabVIEW™. The entire series consists of four volumes that collectively cover basic digital signal processing in a practical and ...
Fundamentals of Acoustic Signal Processing
Fundamentals of Digital Signal Processing
This is a uniquely comprehensive reference that summarizes the state of the art of signal processing theory and techniques for solving emerging problems in neuroscience, and which clearly presents ...
Fundamentals of Natural Gas Processing explores the natural gas industry from the wellhead to the marketplace. It compiles information from the open literature, meeting proceedings, and experts to ...
Ceramic powder synthesis and processing are two of the most important technologies in chemical engineering and the ceramics-related area of materials science. This book covers both the processing and ...
Introduces a statistical theory for extracting information from signals with different sampling rates. This book presents background material, key principles, potential applications and leading-edge ...
Now in a new edition—the most comprehensive, hands-on introduction to digital signal processingThe first edition of Digital Signal Processing and Applications with the TMS320C6713 ...
Understand the RF and Digital Signal Processing Principles Driving Software-defined Radios!Software-defined radio (SDR) technology is a configurable, low cost, and power efficient ...