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Book An Adaptive Detection Algorithm

Download or read book An Adaptive Detection Algorithm written by Edward J. Kelly and published by . This book was released on 1986 with total page 14 pages. Available in PDF, EPUB and Kindle. Book excerpt: A general problem of signal detection in a background of unknown Gaussian noise is addressed, using the techniques of statistical hypothesis testing. Signal presence is sought in one data vector, and another independent set of signal-free data vectors is available which share the unknown covariance matrix of the noise in the vector. A likelihood ratio decision rule is derived and its performance evaluated in both the noise-only and signal-plus-noise cases.

Book Advances in Adaptive Radar Detection and Range Estimation

Download or read book Advances in Adaptive Radar Detection and Range Estimation written by Chengpeng Hao and published by Springer Nature. This book was released on 2021-12-03 with total page 226 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a comprehensive and systematic framework for the design of adaptive architectures, which take advantage of the available a priori information to enhance the detection performance. Moreover, this framework also provides guidelines to develop decision schemes capable of estimating the target position within the range bin. To this end, the readers are driven step-by-step towards those aspects that have to be accounted for at the design stage, starting from the exploitation of system and/or environment information up to the use of target energy leakage (energy spillover), which allows inferring on the target position within the range cell under test.In addition to design issues, this book presents an extensive number of illustrative examples based upon both simulated and real-recorded data. Moreover, the performance analysis is enriched by considerations about the trade-off between performances and computational requirements.Finally, this book could be a valuable resource for PhD students, researchers, professors, and, more generally, engineers working on statistical signal processing and its applications to radar systems.

Book A New Adaptive Detection Algorithm for Power Quality Improvement

Download or read book A New Adaptive Detection Algorithm for Power Quality Improvement written by Lewei Qian and published by . This book was released on 2007 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: ABSTRACT: In this dissertation, a new adaptive harmonic selective detection algorithm is proposed for power quality improvement applications. The adaptive gains of the proposed method can be chosen relatively large to obtain faster convergence. The stability of the proposed method is guaranteed. The adaptive harmonic selective algorithm is analyzed then compared to a popular d-q method. This proposed adaptive method is simple and effective in extracting fundamental and harmonic current information from harmonic load currents. The extracted fundamental or harmonic currents therefore can be used as the reference signals for power quality improvement applications such as harmonic selective cancellation or reactive power compensation. The proposed adaptive algorithm can estimate time varying power system frequency and it also can identify a dc offset in a load current. These are two conditions that the d-q transformation based detection algorithm is incapable of. This adaptive detection method is phase independent and therefore it can be easily applied to three phase systems. Simulation and experimental results verify the good performance of the proposed new adaptive detection method.

Book Machine Learning for Future Wireless Communications

Download or read book Machine Learning for Future Wireless Communications written by Fa-Long Luo and published by John Wiley & Sons. This book was released on 2020-02-10 with total page 490 pages. Available in PDF, EPUB and Kindle. Book excerpt: A comprehensive review to the theory, application and research of machine learning for future wireless communications In one single volume, Machine Learning for Future Wireless Communications provides a comprehensive and highly accessible treatment to the theory, applications and current research developments to the technology aspects related to machine learning for wireless communications and networks. The technology development of machine learning for wireless communications has grown explosively and is one of the biggest trends in related academic, research and industry communities. Deep neural networks-based machine learning technology is a promising tool to attack the big challenge in wireless communications and networks imposed by the increasing demands in terms of capacity, coverage, latency, efficiency flexibility, compatibility, quality of experience and silicon convergence. The author – a noted expert on the topic – covers a wide range of topics including system architecture and optimization, physical-layer and cross-layer processing, air interface and protocol design, beamforming and antenna configuration, network coding and slicing, cell acquisition and handover, scheduling and rate adaption, radio access control, smart proactive caching and adaptive resource allocations. Uniquely organized into three categories: Spectrum Intelligence, Transmission Intelligence and Network Intelligence, this important resource: Offers a comprehensive review of the theory, applications and current developments of machine learning for wireless communications and networks Covers a range of topics from architecture and optimization to adaptive resource allocations Reviews state-of-the-art machine learning based solutions for network coverage Includes an overview of the applications of machine learning algorithms in future wireless networks Explores flexible backhaul and front-haul, cross-layer optimization and coding, full-duplex radio, digital front-end (DFE) and radio-frequency (RF) processing Written for professional engineers, researchers, scientists, manufacturers, network operators, software developers and graduate students, Machine Learning for Future Wireless Communications presents in 21 chapters a comprehensive review of the topic authored by an expert in the field.

Book Parametric and Model Based Adaptive Detection Algorithms for Non Gaussian Interference Backgrounds

Download or read book Parametric and Model Based Adaptive Detection Algorithms for Non Gaussian Interference Backgrounds written by and published by . This book was released on 1999 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This report presents model based adaptive signal processing methods for target detection in a background of non-Gaussian interference. Several candidate algorithms are derived and important insights pertaining to their structure are documented in this report. Performance analysis of these algorithms is discussed in some detail. It is seen that the parametric adaptive matched filter (PAMF) offers the potential for significantly improved performance in non-Gaussian interference scenarios, while leading to considerably lower secondary data support requirements compared to classical adaptive processing methods. This is due to the use of a parametric method that employs a low model order to approximate the interference spectral characteristics. Another reduced rank adaptive algorithm considered in this study is the principal component inverse (PCI) method.

Book Simplified Robust Adaptive Detection and Beamforming for Wireless Communications

Download or read book Simplified Robust Adaptive Detection and Beamforming for Wireless Communications written by Ayman ElNashar and published by John Wiley & Sons. This book was released on 2018-08-20 with total page 424 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents an alternative and simplified approaches for the robust adaptive detection and beamforming in wireless communications. It adopts several systems models including DS/CDMA, OFDM/MIMO with antenna array, and general antenna arrays beamforming model. It presents and analyzes recently developed detection and beamforming algorithms with an emphasis on robustness. In addition, simplified and efficient robust adaptive detection and beamforming techniques are presented and compared with exiting techniques. Practical examples based on the above systems models are provided to exemplify the developed detectors and beamforming algorithms. Moreover, the developed techniques are implemented using MATLAB—and the relevant MATLAB scripts are provided to help the readers to develop and analyze the presented algorithms. em style="mso-bidi-font-style: normal;"Simplified Robust Adaptive Detection and Beamforming for Wireless Communications starts by introducing readers to adaptive signal processing and robust adaptive detection. It then goes on to cover Wireless Systems Models. The robust adaptive detectors and beamformers are implemented using the well-known algorithms including LMS, RLS, IQRD-RLS, RSD, BSCMA, CG, and SD. The robust detection and beamforming are derived based on the existing detectors/beamformers including MOE, PLIC, LCCMA, LCMV, MVDR, BSCMA, and MBER. The adopted cost functions include MSE, BER, CM, MV, and SINR/SNR.

Book Adaptive Detection for Multichannel Signals in Non Ideal Environments

Download or read book Adaptive Detection for Multichannel Signals in Non Ideal Environments written by Zeyu Wang and published by CRC Press. This book was released on 2024-06-14 with total page 195 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book systematically presents adaptive multichannel signal detection in three types of non-ideal environments, including sample-starved scenarios, signal mismatch scenarios, and noise plus subspace interference environments. The authors provide definitions of key concepts, detailed derivations of adaptive multichannel signal detectors, and specific examples for each non-ideal environment. In addition, the possible future trend of adaptive detection methods is discussed, as well as two further research points – namely, the adaptive detection algorithms based on information geometry, and the hybrid approaches that combine adaptive detection algorithms with machine learning algorithms. The book will be of interest to researchers, advanced undergraduates, and graduate students in sonar, radar signal processing, and communications engineering.

Book Adaptive Detection of Multichannel Signals Exploiting Persymmetry

Download or read book Adaptive Detection of Multichannel Signals Exploiting Persymmetry written by Jun Liu and published by CRC Press. This book was released on 2022-12-20 with total page 314 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book offers a systematic presentation of persymmetric adaptive detection, including detector derivations and the definition of key concepts, followed by detailed discussion relating to theoretical underpinnings, design methodology, design considerations, and techniques enabling its practical implementation. The received data for modern radar systems are usually multichannel, namely, vector-valued, or even matrix-valued. Multichannel signal detection in Gaussian backgrounds is a fundamental problem for radar applications. With an overarching focus on persymmetric adaptive detectors, this book presents the mathematical models and design principles necessary for analyzing the behavior of each kind of persymmetric adaptive detector. Building upon that, it also introduces new design approaches and techniques that will guide engineering students as well as radar engineers toward efficient detector solutions, especially in challenging sample-starved environments where training data are limited. This book will be of interest to students, scholars, and engineers in the field of signal processing. It will be especially useful for those who have a solid background in statistical signal processing, multivariate statistical analysis, matrix theory, and mathematical analysis.

Book Adaptive Bandwidth Mode Detection Algorithm

Download or read book Adaptive Bandwidth Mode Detection Algorithm written by Kawkab Dahdah and published by . This book was released on 2009 with total page 51 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book Long Memory in Economics

Download or read book Long Memory in Economics written by Gilles Teyssière and published by Springer Science & Business Media. This book was released on 2006-09-22 with total page 394 pages. Available in PDF, EPUB and Kindle. Book excerpt: Assembles three different strands of long memory analysis: statistical literature on the properties of, and tests for, LRD processes; mathematical literature on the stochastic processes involved; and models from economic theory providing plausible micro foundations for the occurrence of long memory in economics.

Book Detection Algorithms for Wireless Communications

Download or read book Detection Algorithms for Wireless Communications written by Gianluigi Ferrari and published by John Wiley & Sons. This book was released on 2005-12-13 with total page 426 pages. Available in PDF, EPUB and Kindle. Book excerpt: Wireless channels are becoming more and more important, with the future development of wireless ad-hoc networks and the integration of mobile and satellite communications. To this end, algorithmic detection aspects (involved in the physical layer) will become fundamental in the design of a communication system. This book proposes a unified approach to detection for stochastic channels, with particular attention to wireless channels. The core idea is to show that the three main criteria of sequence detection, symbol detection and graph-based detection, can all be described within a general framework. This implies that a detection algorithm based on one criterion can be extended to the other criteria in a systematic manner. Presents a detailed analysis of statistical signal detection for digital signals transmitted over wireless communications Provides a unifying framework for different signal detection algorithms, such as sequence detection, symbol detection and graph-based detection, important for the design of modern digital receivers operating over mobile channels Features the hot topic of graph-based detection Detection Algorithms for Wireless Communications represents a novel contribution with respect to the current literature, with a unique focus on detection algorithms, as such it will prove invaluable to researchers working in academia and industry and in the field of wireless communications, as well as postgraduate students attending advanced courses on mobile communications.

Book Intelligent Information Processing IX

Download or read book Intelligent Information Processing IX written by Zhongzhi Shi and published by Springer. This book was released on 2018-10-10 with total page 448 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 10th IFIP TC 12 International Conference on Intelligent Information Processing, IIP 2018, held in Nanning, China, in October 2018. The 37 full papers and 8 short papers presented were carefully reviewed and selected from 80 submissions. They are organized in topical sections on machine learning, deep learning, multi-agent systems, neural computing and swarm intelligence, natural language processing, recommendation systems, social computing, business intelligence and security, pattern recognition, and image understanding.

Book Advanced Radar Detection Schemes Under Mismatched Signal Models

Download or read book Advanced Radar Detection Schemes Under Mismatched Signal Models written by Francesco Bandiera and published by Morgan & Claypool Publishers. This book was released on 2009-03-08 with total page 105 pages. Available in PDF, EPUB and Kindle. Book excerpt: Adaptive detection of signals embedded in correlated Gaussian noise has been an active field of research in the last decades. This topic is important in many areas of signal processing such as, just to give some examples, radar, sonar, communications, and hyperspectral imaging. Most of the existing adaptive algorithms have been designed following the lead of the derivation of Kelly's detector which assumes perfect knowledge of the target steering vector. However, in realistic scenarios, mismatches are likely to occur due to both environmental and instrumental factors. When a mismatched signal is present in the data under test, conventional algorithms may suffer severe performance degradation. The presence of strong interferers in the cell under test makes the detection task even more challenging. An effective way to cope with this scenario relies on the use of "tunable" detectors, i.e., detectors capable of changing their directivity through the tuning of proper parameters. The aim of this book is to present some recent advances in the design of tunable detectors and the focus is on the so-called two-stage detectors, i.e., adaptive algorithms obtained cascading two detectors with opposite behaviors. We derive exact closed-form expressions for the resulting probability of false alarm and the probability of detection for both matched and mismatched signals embedded in homogeneous Gaussian noise. It turns out that such solutions guarantee a wide operational range in terms of tunability while retaining, at the same time, an overall performance in presence of matched signals commensurate with Kelly's detector. Table of Contents: Introduction / Adaptive Radar Detection of Targets / Adaptive Detection Schemes for Mismatched Signals / Enhanced Adaptive Sidelobe Blanking Algorithms / Conclusions

Book Adaptive Algorithms and Stochastic Approximations

Download or read book Adaptive Algorithms and Stochastic Approximations written by Albert Benveniste and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 373 pages. Available in PDF, EPUB and Kindle. Book excerpt: Adaptive systems are widely encountered in many applications ranging through adaptive filtering and more generally adaptive signal processing, systems identification and adaptive control, to pattern recognition and machine intelligence: adaptation is now recognised as keystone of "intelligence" within computerised systems. These diverse areas echo the classes of models which conveniently describe each corresponding system. Thus although there can hardly be a "general theory of adaptive systems" encompassing both the modelling task and the design of the adaptation procedure, nevertheless, these diverse issues have a major common component: namely the use of adaptive algorithms, also known as stochastic approximations in the mathematical statistics literature, that is to say the adaptation procedure (once all modelling problems have been resolved). The juxtaposition of these two expressions in the title reflects the ambition of the authors to produce a reference work, both for engineers who use these adaptive algorithms and for probabilists or statisticians who would like to study stochastic approximations in terms of problems arising from real applications. Hence the book is organised in two parts, the first one user-oriented, and the second providing the mathematical foundations to support the practice described in the first part. The book covers the topcis of convergence, convergence rate, permanent adaptation and tracking, change detection, and is illustrated by various realistic applications originating from these areas of applications.

Book Adaptive Detection of Approximately Duplicate Database Records and the Database Integration Approach to Information Discovery

Download or read book Adaptive Detection of Approximately Duplicate Database Records and the Database Integration Approach to Information Discovery written by Alvaro Edmundo Monge and published by . This book was released on 1997 with total page 232 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book Adaptive Radar Detection and Estimation

Download or read book Adaptive Radar Detection and Estimation written by Simon Haykin and published by Wiley-Interscience. This book was released on 1992-04-15 with total page 504 pages. Available in PDF, EPUB and Kindle. Book excerpt: Adaptive processing in a radar environment is necessary due to its inherently nonstable nature. A detailed mathematical treatment of the important issues in adaptive radar detection and estimation is offered. Since much of the material presented has not appeared in book form, you'll find this work fills an important gap in the known literature. Following an overview of the subject, contributors develop model-based techniques for the detection of radar targets in the presence of clutter; discuss minimum variance beamforming techniques; consider maximum likelihood bearing estimation in beamspace for an adaptive phased array radar; present an algorithm for angle-of-arrival estimation; and describe the method of multiple windows for spectrum estimation.