Download or read book Special Issue Machine Learning for Signal Processing 2010 written by International Workshop on Machine Learning for Signal Processing. 20, 2010, Kittilä and published by . This book was released on 2012 with total page 128 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Special Issue Machine Learning for Signal Processing written by and published by . This book was released on 2011 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Special Issue on Machine Learning for Signal Processing written by David J. Miller and published by . This book was released on 2004 with total page 180 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Special Issue on Machine Learning Methods in Signal Processing written by Meir Feder and published by . This book was released on 2003 with total page 204 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Signal Processing and Machine Learning Theory written by Paulo S.R. Diniz and published by Elsevier. This book was released on 2023-07-10 with total page 1236 pages. Available in PDF, EPUB and Kindle. Book excerpt: Signal Processing and Machine Learning Theory, authored by world-leading experts, reviews the principles, methods and techniques of essential and advanced signal processing theory. These theories and tools are the driving engines of many current and emerging research topics and technologies, such as machine learning, autonomous vehicles, the internet of things, future wireless communications, medical imaging, etc. Provides quick tutorial reviews of important and emerging topics of research in signal processing-based tools Presents core principles in signal processing theory and shows their applications Discusses some emerging signal processing tools applied in machine learning methods References content on core principles, technologies, algorithms and applications Includes references to journal articles and other literature on which to build further, more specific, and detailed knowledge
Download or read book Machine Learning for Signal Processing 2010 written by International Workshop on Machine Learning for Signal Processing and published by . This book was released on 2012 with total page 128 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Academic Press Library in Signal Processing written by Paulo S.R. Diniz and published by Academic Press. This book was released on 2013-09-21 with total page 1559 pages. Available in PDF, EPUB and Kindle. Book excerpt: This first volume, edited and authored by world leading experts, gives a review of the principles, methods and techniques of important and emerging research topics and technologies in machine learning and advanced signal processing theory. With this reference source you will: Quickly grasp a new area of research Understand the underlying principles of a topic and its application Ascertain how a topic relates to other areas and learn of the research issues yet to be resolved Quick tutorial reviews of important and emerging topics of research in machine learning Presents core principles in signal processing theory and shows their applications Reference content on core principles, technologies, algorithms and applications Comprehensive references to journal articles and other literature on which to build further, more specific and detailed knowledge Edited by leading people in the field who, through their reputation, have been able to commission experts to write on a particular topic
Download or read book Financial Signal Processing and Machine Learning written by Ali N. Akansu and published by John Wiley & Sons. This book was released on 2016-04-21 with total page 312 pages. Available in PDF, EPUB and Kindle. Book excerpt: The modern financial industry has been required to deal with large and diverse portfolios in a variety of asset classes often with limited market data available. Financial Signal Processing and Machine Learning unifies a number of recent advances made in signal processing and machine learning for the design and management of investment portfolios and financial engineering. This book bridges the gap between these disciplines, offering the latest information on key topics including characterizing statistical dependence and correlation in high dimensions, constructing effective and robust risk measures, and their use in portfolio optimization and rebalancing. The book focuses on signal processing approaches to model return, momentum, and mean reversion, addressing theoretical and implementation aspects. It highlights the connections between portfolio theory, sparse learning and compressed sensing, sparse eigen-portfolios, robust optimization, non-Gaussian data-driven risk measures, graphical models, causal analysis through temporal-causal modeling, and large-scale copula-based approaches. Key features: Highlights signal processing and machine learning as key approaches to quantitative finance. Offers advanced mathematical tools for high-dimensional portfolio construction, monitoring, and post-trade analysis problems. Presents portfolio theory, sparse learning and compressed sensing, sparsity methods for investment portfolios. including eigen-portfolios, model return, momentum, mean reversion and non-Gaussian data-driven risk measures with real-world applications of these techniques. Includes contributions from leading researchers and practitioners in both the signal and information processing communities, and the quantitative finance community.
Download or read book Informatics and Machine Learning written by Stephen Winters-Hilt and published by John Wiley & Sons. This book was released on 2022-01-06 with total page 596 pages. Available in PDF, EPUB and Kindle. Book excerpt: Informatics and Machine Learning Discover a thorough exploration of how to use computational, algorithmic, statistical, and informatics methods to analyze digital data Informatics and Machine Learning: From Martingales to Metaheuristics delivers an interdisciplinary presentation on how analyze any data captured in digital form. The book describes how readers can conduct analyses of text, general sequential data, experimental observations over time, stock market and econometric histories, or symbolic data, like genomes. It contains large amounts of sample code to demonstrate the concepts contained within and assist with various levels of project work. The book offers a complete presentation of the mathematical underpinnings of a wide variety of forms of data analysis and provides extensive examples of programming implementations. It is based on two decades worth of the distinguished author’s teaching and industry experience. A thorough introduction to probabilistic reasoning and bioinformatics, including Python shell scripting to obtain data counts, frequencies, probabilities, and anomalous statistics, or use with Bayes’ rule An exploration of information entropy and statistical measures, including Shannon entropy, relative entropy, maximum entropy (maxent), and mutual information A practical discussion of ad hoc, ab initio, and bootstrap signal acquisition methods, with examples from genome analytics and signal analytics Perfect for undergraduate and graduate students in machine learning and data analytics programs, Informatics and Machine Learning: From Martingales to Metaheuristics will also earn a place in the libraries of mathematicians, engineers, computer scientists, and life scientists with an interest in those subjects.
Download or read book EEG Signal Processing and Machine Learning written by Saeid Sanei and published by John Wiley & Sons. This book was released on 2021-09-27 with total page 756 pages. Available in PDF, EPUB and Kindle. Book excerpt: EEG Signal Processing and Machine Learning Explore cutting edge techniques at the forefront of electroencephalogram research and artificial intelligence from leading voices in the field The newly revised Second Edition of EEG Signal Processing and Machine Learning delivers an inclusive and thorough exploration of new techniques and outcomes in electroencephalogram (EEG) research in the areas of analysis, processing, and decision making about a variety of brain states, abnormalities, and disorders using advanced signal processing and machine learning techniques. The book content is substantially increased upon that of the first edition and, while it retains what made the first edition so popular, is composed of more than 50% new material. The distinguished authors have included new material on tensors for EEG analysis and sensor fusion, as well as new chapters on mental fatigue, sleep, seizure, neurodevelopmental diseases, BCI, and psychiatric abnormalities. In addition to including a comprehensive chapter on machine learning, machine learning applications have been added to almost all the chapters. Moreover, multimodal brain screening, such as EEG-fMRI, and brain connectivity have been included as two new chapters in this new edition. Readers will also benefit from the inclusion of: A thorough introduction to EEGs, including neural activities, action potentials, EEG generation, brain rhythms, and EEG recording and measurement An exploration of brain waves, including their generation, recording, and instrumentation, abnormal EEG patterns and the effects of ageing and mental disorders A treatment of mathematical models for normal and abnormal EEGs Discussions of the fundamentals of EEG signal processing, including statistical properties, linear and nonlinear systems, frequency domain approaches, tensor factorization, diffusion adaptive filtering, deep neural networks, and complex-valued signal processing Perfect for biomedical engineers, neuroscientists, neurophysiologists, psychiatrists, engineers, students and researchers in the above areas, the Second Edition of EEG Signal Processing and Machine Learning will also earn a place in the libraries of undergraduate and postgraduate students studying Biomedical Engineering, Neuroscience and Epileptology.
Download or read book Principles of Cognitive Radio written by Ezio Biglieri and published by Cambridge University Press. This book was released on 2013 with total page 327 pages. Available in PDF, EPUB and Kindle. Book excerpt: Expert authors draw on fundamental theory to explain the core principles and key design considerations for developing cognitive radio systems.
Download or read book Advances in Machine Learning and Signal Processing written by Ping Jack Soh and published by Springer. This book was released on 2016-06-18 with total page 309 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents important research findings and recent innovations in the field of machine learning and signal processing. A wide range of topics relating to machine learning and signal processing techniques and their applications are addressed in order to provide both researchers and practitioners with a valuable resource documenting the latest advances and trends. The book comprises a careful selection of the papers submitted to the 2015 International Conference on Machine Learning and Signal Processing (MALSIP 2015), which was held on 15–17 December 2015 in Ho Chi Minh City, Vietnam with the aim of offering researchers, academicians, and practitioners an ideal opportunity to disseminate their findings and achievements. All of the included contributions were chosen by expert peer reviewers from across the world on the basis of their interest to the community. In addition to presenting the latest in design, development, and research, the book provides access to numerous new algorithms for machine learning and signal processing for engineering problems.
Download or read book Machine Learning Methods for Signal Image and Speech Processing written by M.A. Jabbar and published by CRC Press. This book was released on 2022-09-01 with total page 257 pages. Available in PDF, EPUB and Kindle. Book excerpt: The signal processing (SP) landscape has been enriched by recent advances in artificial intelligence (AI) and machine learning (ML), yielding new tools for signal estimation, classification, prediction, and manipulation. Layered signal representations, nonlinear function approximation and nonlinear signal prediction are now feasible at very large scale in both dimensionality and data size. These are leading to significant performance gains in a variety of long-standing problem domains like speech and Image analysis. As well as providing the ability to construct new classes of nonlinear functions (e.g., fusion, nonlinear filtering). This book will help academics, researchers, developers, graduate and undergraduate students to comprehend complex SP data across a wide range of topical application areas such as social multimedia data collected from social media networks, medical imaging data, data from Covid tests etc. This book focuses on AI utilization in the speech, image, communications and yirtual reality domains.
Download or read book Deep Learning written by Li Deng and published by . This book was released on 2014 with total page 212 pages. Available in PDF, EPUB and Kindle. Book excerpt: Provides an overview of general deep learning methodology and its applications to a variety of signal and information processing tasks
Download or read book Machine Learning Theory and Applications written by and published by Newnes. This book was released on 2013-05-16 with total page 551 pages. Available in PDF, EPUB and Kindle. Book excerpt: Statistical learning and analysis techniques have become extremely important today, given the tremendous growth in the size of heterogeneous data collections and the ability to process it even from physically distant locations. Recent advances made in the field of machine learning provide a strong framework for robust learning from the diverse corpora and continue to impact a variety of research problems across multiple scientific disciplines. The aim of this handbook is to familiarize beginners as well as experts with some of the recent techniques in this field.The Handbook is divided in two sections: Theory and Applications, covering machine learning, data analytics, biometrics, document recognition and security. Very relevant to current research challenges faced in various fields Self-contained reference to machine learning Emphasis on applications-oriented techniques
Download or read book Special Issue on Signal Processing Selected Papers from the TSP 2010 Conference written by and published by . This book was released on 2011 with total page 183 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Artificial Intelligence for Signal Processing and Wireless Communication written by Abhinav Sharma and published by Walter de Gruyter GmbH & Co KG. This book was released on 2022-04-04 with total page 248 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book focuses on artifi cial intelligence in the field of digital signal processing and wireless communication. The implementation of machine learning and deep learning in audio, image, and video processing is presented, while adaptive signal processing and biomedical signal processing are also explored through DL algorithms, as well as 5G and green communication. Finally, metaheuristic algorithms of related mathematical problems are explored.
