Introduction to Nonparametric Detection with Applications

Introduction to Nonparametric Detection with Applications
Author: Jerry D. Gibson
Publisher: Academic Press
Total Pages: 255
Release: 1976-01-22
Genre: Computers
ISBN: 0080956289

Even with the advances in signal processing and digital communications, robustness to uncertain channel statistics continues to be a fundamental issue in the design and performance analysis of today's communications, radar, and sonar systems. The variability of digital communications systems consistently challenges the communications system designer, while new applications have channels that almost defy accurate modeling. As a result, parametric detectors, which are excellent when model assumptions are satisfied, do not maintain the satisfactory performance necessary for detection. This core IEEE Press reissue is the only book devoted solely to nonparametric detection - the key to maintaining good performance over a wide range of conditions. Throughout, the authors employ the classical Neyman-Pearson approach, which is widely applicable to detection problems in communications, radar, sonar, acoustics, and geophysics. Topics covered include: nonparametric detection theory, basic detection theory, one-input and two-input detectors and performance, tied observations, dependent sample performance, and engineering applications.

Introduction to Nonparametric Statistics for the Biological Sciences Using R

Introduction to Nonparametric Statistics for the Biological Sciences Using R
Author: Thomas W. MacFarland
Publisher: Springer
Total Pages: 341
Release: 2016-07-06
Genre: Medical
ISBN: 3319306340

This book contains a rich set of tools for nonparametric analyses, and the purpose of this text is to provide guidance to students and professional researchers on how R is used for nonparametric data analysis in the biological sciences: To introduce when nonparametric approaches to data analysis are appropriate To introduce the leading nonparametric tests commonly used in biostatistics and how R is used to generate appropriate statistics for each test To introduce common figures typically associated with nonparametric data analysis and how R is used to generate appropriate figures in support of each data set The book focuses on how R is used to distinguish between data that could be classified as nonparametric as opposed to data that could be classified as parametric, with both approaches to data classification covered extensively. Following an introductory lesson on nonparametric statistics for the biological sciences, the book is organized into eight self-contained lessons on various analyses and tests using R to broadly compare differences between data sets and statistical approach.

Nonparametric Statistics

Nonparametric Statistics
Author: Gregory W. Corder
Publisher: John Wiley & Sons
Total Pages: 288
Release: 2014-04-14
Genre: Mathematics
ISBN: 1118840429

“...a very useful resource for courses in nonparametric statistics in which the emphasis is on applications rather than on theory. It also deserves a place in libraries of all institutions where introductory statistics courses are taught." –CHOICE This Second Edition presents a practical and understandable approach that enhances and expands the statistical toolset for readers. This book includes: New coverage of the sign test and the Kolmogorov-Smirnov two-sample test in an effort to offer a logical and natural progression to statistical power SPSS® (Version 21) software and updated screen captures to demonstrate how to perform and recognize the steps in the various procedures Data sets and odd-numbered solutions provided in an appendix, and tables of critical values Supplementary material to aid in reader comprehension, which includes: narrated videos and screen animations with step-by-step instructions on how to follow the tests using SPSS; online decision trees to help users determine the needed type of statistical test; and additional solutions not found within the book.

An Introduction to Signal Detection and Estimation

An Introduction to Signal Detection and Estimation
Author: H. Vincent Poor
Publisher: Springer Science & Business Media
Total Pages: 405
Release: 2013-03-14
Genre: Technology & Engineering
ISBN: 1475723415

Essential background reading for engineers and scientists working in such fields as communications, control, signal, and image processing, radar and sonar, radio astronomy, seismology, remote sensing, and instrumentation. The book can be used as a textbook for a single course, as well as a combination of an introductory and an advanced course, or even for two separate courses, one in signal detection, the other in estimation.

Introduction to Nonparametric Estimation

Introduction to Nonparametric Estimation
Author: Alexandre B. Tsybakov
Publisher: Springer Science & Business Media
Total Pages: 222
Release: 2008-10-22
Genre: Mathematics
ISBN: 0387790527

Developed from lecture notes and ready to be used for a course on the graduate level, this concise text aims to introduce the fundamental concepts of nonparametric estimation theory while maintaining the exposition suitable for a first approach in the field.

Topics in Nonparametric Statistics

Topics in Nonparametric Statistics
Author: Michael G. Akritas
Publisher: Springer
Total Pages: 369
Release: 2014-12-02
Genre: Mathematics
ISBN: 1493905694

This volume is composed of peer-reviewed papers that have developed from the First Conference of the International Society for Non Parametric Statistics (ISNPS). This inaugural conference took place in Chalkidiki, Greece, June 15-19, 2012. It was organized with the co-sponsorship of the IMS, the ISI and other organizations. M.G. Akritas, S.N. Lahiri and D.N. Politis are the first executive committee members of ISNPS and the editors of this volume. ISNPS has a distinguished Advisory Committee that includes Professors R.Beran, P.Bickel, R. Carroll, D. Cook, P. Hall, R. Johnson, B. Lindsay, E. Parzen, P. Robinson, M. Rosenblatt, G. Roussas, T. SubbaRao and G. Wahba. The Charting Committee of ISNPS consists of more than 50 prominent researchers from all over the world. The chapters in this volume bring forth recent advances and trends in several areas of nonparametric statistics. In this way, the volume facilitates the exchange of research ideas, promotes collaboration among researchers from all over the world and contributes to the further development of the field. The conference program included over 250 talks, including special invited talks, plenary talks and contributed talks on all areas of nonparametric statistics. Out of these talks, some of the most pertinent ones have been refereed and developed into chapters that share both research and developments in the field.

Digital Signal Processing Fundamentals

Digital Signal Processing Fundamentals
Author: Vijay Madisetti
Publisher: CRC Press
Total Pages: 904
Release: 2017-12-19
Genre: Technology & Engineering
ISBN: 1420046071

Now available in a three-volume set, this updated and expanded edition of the bestselling The Digital Signal Processing Handbook continues to provide the engineering community with authoritative coverage of the fundamental and specialized aspects of information-bearing signals in digital form. Encompassing essential background material, technical details, standards, and software, the second edition reflects cutting-edge information on signal processing algorithms and protocols related to speech, audio, multimedia, and video processing technology associated with standards ranging from WiMax to MP3 audio, low-power/high-performance DSPs, color image processing, and chips on video. Drawing on the experience of leading engineers, researchers, and scholars, the three-volume set contains 29 new chapters that address multimedia and Internet technologies, tomography, radar systems, architecture, standards, and future applications in speech, acoustics, video, radar, and telecommunications. Emphasizing theoretical concepts, Digital Signal Processing Fundamentals provides comprehensive coverage of the basic foundations of DSP and includes the following parts: Signals and Systems; Signal Representation and Quantization; Fourier Transforms; Digital Filtering; Statistical Signal Processing; Adaptive Filtering; Inverse Problems and Signal Reconstruction; and Time–Frequency and Multirate Signal Processing.

Biomedical Signals, Imaging, and Informatics

Biomedical Signals, Imaging, and Informatics
Author: Joseph D. Bronzino
Publisher: CRC Press
Total Pages: 1416
Release: 2014-12-16
Genre: Medical
ISBN: 1439825289

As the third volume of The Biomedical Engineering Handbook, Fourth Edition, this book covers broad areas such as biosignal processing, medical imaging, infrared imaging, and medical informatics. More than three dozen specific topics are examined including biomedical signal acquisition, thermographs, infrared cameras, mammography, computed tomography, positron-emission tomography, magnetic resonance imaging, hospital information systems, and computer-based patient records. The material is presented in a systematic manner and has been updated to reflect the latest applications and research findings.

Structural Health Monitoring 2003

Structural Health Monitoring 2003
Author: Fu-Kuo Chang
Publisher: DEStech Publications, Inc
Total Pages: 1592
Release: 2003
Genre: Technology & Engineering
ISBN: 9781932078206

Important new information on sensors, monitoring, prognosis, networking, and planning for safety and maintenance.

Advanced Theory of Signal Detection

Advanced Theory of Signal Detection
Author: Iickho Song
Publisher: Springer Science & Business Media
Total Pages: 416
Release: 2002-03-26
Genre: Computers
ISBN: 9783540430643

This book contains a number of problems of signal detection theory. A generalized observation model for signal detection problems is included. The model includes several interesting and common special cases such as those describing additive noise, multiplicative noise, and signal-dependent noise. The model can also describe composite signals in addition to the usual known (deterministic) signals and random (stochastic) signals. Locally optimum (LO) and locally optimum rank (LOR) detectors for known and random signals in the model are discussed, and original results are obtained. Other approaches to detection of signals are also discussed.