Machine Intelligence And Signal Analysis

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Machine Intelligence and Signal Analysis

Author : M. Tanveer
Publisher : Springer
ISBN 13 : 981130923X
Total Pages : 767 pages
Book Rating : 4.8/5 (113 download)

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Book Synopsis Machine Intelligence and Signal Analysis by : M. Tanveer

Download or read book Machine Intelligence and Signal Analysis written by M. Tanveer and published by Springer. This book was released on 2018-08-07 with total page 767 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book covers the most recent developments in machine learning, signal analysis, and their applications. It covers the topics of machine intelligence such as: deep learning, soft computing approaches, support vector machines (SVMs), least square SVMs (LSSVMs) and their variants; and covers the topics of signal analysis such as: biomedical signals including electroencephalogram (EEG), magnetoencephalography (MEG), electrocardiogram (ECG) and electromyogram (EMG) as well as other signals such as speech signals, communication signals, vibration signals, image, and video. Further, it analyzes normal and abnormal categories of real-world signals, for example normal and epileptic EEG signals using numerous classification techniques. The book is envisioned for researchers and graduate students in Computer Science and Engineering, Electrical Engineering, Applied Mathematics, and Biomedical Signal Processing.

Machine Learning in Signal Processing

Author : Sudeep Tanwar
Publisher : CRC Press
ISBN 13 : 1000487814
Total Pages : 488 pages
Book Rating : 4.0/5 (4 download)

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Book Synopsis Machine Learning in Signal Processing by : Sudeep Tanwar

Download or read book Machine Learning in Signal Processing written by Sudeep Tanwar and published by CRC Press. This book was released on 2021-12-10 with total page 488 pages. Available in PDF, EPUB and Kindle. Book excerpt: Machine Learning in Signal Processing: Applications, Challenges, and the Road Ahead offers a comprehensive approach toward research orientation for familiarizing signal processing (SP) concepts to machine learning (ML). ML, as the driving force of the wave of artificial intelligence (AI), provides powerful solutions to many real-world technical and scientific challenges. This book will present the most recent and exciting advances in signal processing for ML. The focus is on understanding the contributions of signal processing and ML, and its aim to solve some of the biggest challenges in AI and ML. FEATURES Focuses on addressing the missing connection between signal processing and ML Provides a one-stop guide reference for readers Oriented toward material and flow with regards to general introduction and technical aspects Comprehensively elaborates on the material with examples and diagrams This book is a complete resource designed exclusively for advanced undergraduate students, post-graduate students, research scholars, faculties, and academicians of computer science and engineering, computer science and applications, and electronics and telecommunication engineering.

Machine Intelligence and Signal Processing

Author : Sonali Agarwal
Publisher : Springer Nature
ISBN 13 : 981151366X
Total Pages : 466 pages
Book Rating : 4.8/5 (115 download)

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Book Synopsis Machine Intelligence and Signal Processing by : Sonali Agarwal

Download or read book Machine Intelligence and Signal Processing written by Sonali Agarwal and published by Springer Nature. This book was released on 2020-02-25 with total page 466 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book features selected high-quality research papers presented at the International Conference on Machine Intelligence and Signal Processing (MISP 2019), held at the Indian Institute of Technology, Allahabad, India, on September 7–10, 2019. The book covers the latest advances in the fields of machine learning, big data analytics, signal processing, computational learning theory, and their real-time applications. The topics covered include support vector machines (SVM) and variants like least-squares SVM (LS-SVM) and twin SVM (TWSVM), extreme learning machine (ELM), artificial neural network (ANN), and other areas in machine learning. Further, it discusses the real-time challenges involved in processing big data and adapting the algorithms dynamically to improve the computational efficiency. Lastly, it describes recent developments in processing signals, for instance, signals generated from IoT devices, smart systems, speech, and videos and addresses biomedical signal processing: electrocardiogram (ECG) and electroencephalogram (EEG).

Signal Processing and Machine Learning with Applications

Author : Michael M. Richter
Publisher : Springer
ISBN 13 : 9783319453712
Total Pages : 0 pages
Book Rating : 4.4/5 (537 download)

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Book Synopsis Signal Processing and Machine Learning with Applications by : Michael M. Richter

Download or read book Signal Processing and Machine Learning with Applications written by Michael M. Richter and published by Springer. This book was released on 2022-10-01 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Signal processing captures, interprets, describes and manipulates physical phenomena. Mathematics, statistics, probability, and stochastic processes are among the signal processing languages we use to interpret real-world phenomena, model them, and extract useful information. This book presents different kinds of signals humans use and applies them for human machine interaction to communicate. Signal Processing and Machine Learning with Applications presents methods that are used to perform various Machine Learning and Artificial Intelligence tasks in conjunction with their applications. It is organized in three parts: Realms of Signal Processing; Machine Learning and Recognition; and Advanced Applications and Artificial Intelligence. The comprehensive coverage is accompanied by numerous examples, questions with solutions, with historical notes. The book is intended for advanced undergraduate and postgraduate students, researchers and practitioners who are engaged with signal processing, machine learning and the applications.

Machine Learning in Bio-Signal Analysis and Diagnostic Imaging

Author : Nilanjan Dey
Publisher : Academic Press
ISBN 13 : 012816087X
Total Pages : 345 pages
Book Rating : 4.1/5 (281 download)

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Book Synopsis Machine Learning in Bio-Signal Analysis and Diagnostic Imaging by : Nilanjan Dey

Download or read book Machine Learning in Bio-Signal Analysis and Diagnostic Imaging written by Nilanjan Dey and published by Academic Press. This book was released on 2018-11-30 with total page 345 pages. Available in PDF, EPUB and Kindle. Book excerpt: Machine Learning in Bio-Signal Analysis and Diagnostic Imaging presents original research on the advanced analysis and classification techniques of biomedical signals and images that cover both supervised and unsupervised machine learning models, standards, algorithms, and their applications, along with the difficulties and challenges faced by healthcare professionals in analyzing biomedical signals and diagnostic images. These intelligent recommender systems are designed based on machine learning, soft computing, computer vision, artificial intelligence and data mining techniques. Classification and clustering techniques, such as PCA, SVM, techniques, Naive Bayes, Neural Network, Decision trees, and Association Rule Mining are among the approaches presented. The design of high accuracy decision support systems assists and eases the job of healthcare practitioners and suits a variety of applications. Integrating Machine Learning (ML) technology with human visual psychometrics helps to meet the demands of radiologists in improving the efficiency and quality of diagnosis in dealing with unique and complex diseases in real time by reducing human errors and allowing fast and rigorous analysis. The book's target audience includes professors and students in biomedical engineering and medical schools, researchers and engineers. Examines a variety of machine learning techniques applied to bio-signal analysis and diagnostic imaging Discusses various methods of using intelligent systems based on machine learning, soft computing, computer vision, artificial intelligence and data mining Covers the most recent research on machine learning in imaging analysis and includes applications to a number of domains

Machine Intelligence Techniques for Data Analysis and Signal Processing

Author : Dilip Singh Sisodia
Publisher : Springer Nature
ISBN 13 : 9819900859
Total Pages : 879 pages
Book Rating : 4.8/5 (199 download)

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Book Synopsis Machine Intelligence Techniques for Data Analysis and Signal Processing by : Dilip Singh Sisodia

Download or read book Machine Intelligence Techniques for Data Analysis and Signal Processing written by Dilip Singh Sisodia and published by Springer Nature. This book was released on 2023-05-30 with total page 879 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book comprises the proceedings of the 4th International Conference on Machine Intelligence and Signal Processing (MISP2022). The contents of this book focus on research advancements in machine intelligence, signal processing, and applications. The book covers the real-time challenges involved while processing big data analytics and stream processing with the integration of smart data computing services and interconnectivity. It also includes the progress in signal processing to process the normal and abnormal categories of real-world signals such as signals generated from IoT devices, smart systems, speech, and videos and involves biomedical signal processing: electrocardiogram (ECG), electroencephalogram (EEG), magnetoencephalography (MEG), electromyogram (EMG), etc. This book proves a valuable resource for those in academia and industry.

Machine Learning Methods for Signal, Image and Speech Processing

Author : M.A. Jabbar
Publisher : CRC Press
ISBN 13 : 1000794741
Total Pages : 257 pages
Book Rating : 4.0/5 (7 download)

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Book Synopsis Machine Learning Methods for Signal, Image and Speech Processing by : M.A. Jabbar

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.

Advanced Machine Intelligence and Signal Processing

Author : Deepak Gupta
Publisher : Springer Nature
ISBN 13 : 9811908400
Total Pages : 859 pages
Book Rating : 4.8/5 (119 download)

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Book Synopsis Advanced Machine Intelligence and Signal Processing by : Deepak Gupta

Download or read book Advanced Machine Intelligence and Signal Processing written by Deepak Gupta and published by Springer Nature. This book was released on 2022-06-25 with total page 859 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book covers the latest advancements in the areas of machine learning, computer vision, pattern recognition, computational learning theory, big data analytics, network intelligence, signal processing, and their applications in real world. The topics covered in machine learning involve feature extraction, variants of support vector machine (SVM), extreme learning machine (ELM), artificial neural network (ANN), and other areas in machine learning. The mathematical analysis of computer vision and pattern recognition involves the use of geometric techniques, scene understanding and modeling from video, 3D object recognition, localization and tracking, medical image analysis, and so on. Computational learning theory involves different kinds of learning like incremental, online, reinforcement, manifold, multitask, semi-supervised, etc. Further, it covers the real-time challenges involved while processing big data analytics and stream processing with the integration of smart data computing services and interconnectivity. Additionally, it covers the recent developments to network intelligence for analyzing the network information and thereby adapting the algorithms dynamically to improve the efficiency. In the last, it includes the progress in signal processing to process the normal and abnormal categories of real-world signals, for instance signals generated from IoT devices, smart systems, speech, videos, etc., and involves biomedical signal processing: electrocardiogram (ECG), electroencephalogram (EEG), magnetoencephalography (MEG), and electromyogram (EMG).

Biomedical Signal Processing and Artificial Intelligence in Healthcare

Author : Walid A. Zgallai
Publisher : Academic Press
ISBN 13 : 0128189479
Total Pages : 270 pages
Book Rating : 4.1/5 (281 download)

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Book Synopsis Biomedical Signal Processing and Artificial Intelligence in Healthcare by : Walid A. Zgallai

Download or read book Biomedical Signal Processing and Artificial Intelligence in Healthcare written by Walid A. Zgallai and published by Academic Press. This book was released on 2020-07-29 with total page 270 pages. Available in PDF, EPUB and Kindle. Book excerpt: Biomedical Signal Processing and Artificial Intelligence in Healthcare is a new volume in the Developments in Biomedical Engineering and Bioelectronics series. This volume covers the basics of biomedical signal processing and artificial intelligence. It explains the role of machine learning in relation to processing biomedical signals and the applications in medicine and healthcare. The book provides background to statistical analysis in biomedical systems. Several types of biomedical signals are introduced and analyzed, including ECG and EEG signals. The role of Deep Learning, Neural Networks, and the implications of the expansion of artificial intelligence is covered. Biomedical Images are also introduced and processed, including segmentation, classification, and detection. This book covers different aspects of signals, from the use of hardware and software, and making use of artificial intelligence in problem solving.Dr Zgallai’s book has up to date coverage where readers can find the latest information, easily explained, with clear examples and illustrations. The book includes examples on the application of signal and image processing employing artificial intelligence to Alzheimer, Parkinson, ADHD, autism, and sleep disorders, as well as ECG and EEG signals. Developments in Biomedical Engineering and Bioelectronics is a 10-volume series which covers recent developments, trends and advances in this field. Edited by leading academics in the field, and taking a multidisciplinary approach, this series is a forum for cutting-edge, contemporary review articles and contributions from key ‘up-and-coming’ academics across the full subject area. The series serves a wide audience of university faculty, researchers and students, as well as industry practitioners. Coverage of the subject area and the latest advances and applications in biomedical signal processing and Artificial Intelligence Contributions by recognized researchers and field leaders On-line presentations, tutorials, application and algorithm examples

Financial Signal Processing and Machine Learning

Author : Ali N. Akansu
Publisher : John Wiley & Sons
ISBN 13 : 1118745639
Total Pages : 312 pages
Book Rating : 4.1/5 (187 download)

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Book Synopsis Financial Signal Processing and Machine Learning by : Ali N. Akansu

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.

Machine Learning in Signal Processing

Author : Sudeep Tanwar
Publisher : CRC Press
ISBN 13 : 1000487792
Total Pages : 388 pages
Book Rating : 4.0/5 (4 download)

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Book Synopsis Machine Learning in Signal Processing by : Sudeep Tanwar

Download or read book Machine Learning in Signal Processing written by Sudeep Tanwar and published by CRC Press. This book was released on 2021-12-10 with total page 388 pages. Available in PDF, EPUB and Kindle. Book excerpt: Machine Learning in Signal Processing: Applications, Challenges, and the Road Ahead offers a comprehensive approach toward research orientation for familiarizing signal processing (SP) concepts to machine learning (ML). ML, as the driving force of the wave of artificial intelligence (AI), provides powerful solutions to many real-world technical and scientific challenges. This book will present the most recent and exciting advances in signal processing for ML. The focus is on understanding the contributions of signal processing and ML, and its aim to solve some of the biggest challenges in AI and ML. FEATURES Focuses on addressing the missing connection between signal processing and ML Provides a one-stop guide reference for readers Oriented toward material and flow with regards to general introduction and technical aspects Comprehensively elaborates on the material with examples and diagrams This book is a complete resource designed exclusively for advanced undergraduate students, post-graduate students, research scholars, faculties, and academicians of computer science and engineering, computer science and applications, and electronics and telecommunication engineering.

Machine Intelligence and Signal Processing

Author : Richa Singh
Publisher : Springer
ISBN 13 : 8132226259
Total Pages : 163 pages
Book Rating : 4.1/5 (322 download)

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Book Synopsis Machine Intelligence and Signal Processing by : Richa Singh

Download or read book Machine Intelligence and Signal Processing written by Richa Singh and published by Springer. This book was released on 2015-10-01 with total page 163 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book comprises chapters on key problems in machine learning and signal processing arenas. The contents of the book are a result of a 2014 Workshop on Machine Intelligence and Signal Processing held at the Indraprastha Institute of Information Technology. Traditionally, signal processing and machine learning were considered to be separate areas of research. However in recent times the two communities are getting closer. In a very abstract fashion, signal processing is the study of operator design. The contributions of signal processing had been to device operators for restoration, compression, etc. Applied Mathematicians were more interested in operator analysis. Nowadays signal processing research is gravitating towards operator learning – instead of designing operators based on heuristics (for example wavelets), the trend is to learn these operators (for example dictionary learning). And thus, the gap between signal processing and machine learning is fast converging. The 2014 Workshop on Machine Intelligence and Signal Processing was one of the few unique events that are focused on the convergence of the two fields. The book is comprised of chapters based on the top presentations at the workshop. This book has three chapters on various topics of biometrics – two are on face detection and one on iris recognition; all from top researchers in their field. There are four chapters on different biomedical signal / image processing problems. Two of these are on retinal vessel classification and extraction; one on biomedical signal acquisition and the fourth one on region detection. There are three chapters on data analysis – a topic gaining immense popularity in industry and academia. One of these shows a novel use of compressed sensing in missing sales data interpolation. Another chapter is on spam detection and the third one is on simple one-shot movie rating prediction. Four other chapters cover various cutting edge miscellaneous topics on character recognition, software effort prediction, speech recognition and non-linear sparse recovery. The contents of this book will prove useful to researchers, professionals and students in the domains of machine learning and signal processing.

Machine Learning for Signal Processing

Author : Max A. Little
Publisher : Oxford University Press, USA
ISBN 13 : 0198714939
Total Pages : 378 pages
Book Rating : 4.1/5 (987 download)

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Book Synopsis Machine Learning for Signal Processing by : Max A. Little

Download or read book Machine Learning for Signal Processing written by Max A. Little and published by Oxford University Press, USA. This book was released on 2019 with total page 378 pages. Available in PDF, EPUB and Kindle. Book excerpt: Describes in detail the fundamental mathematics and algorithms of machine learning (an example of artificial intelligence) and signal processing, two of the most important and exciting technologies in the modern information economy. Builds up concepts gradually so that the ideas and algorithms can be implemented in practical software applications.

Signal Processing and Machine Learning for Brain-Machine Interfaces

Author : Toshihisa Tanaka
Publisher : Institution of Engineering and Technology
ISBN 13 : 1785613987
Total Pages : 355 pages
Book Rating : 4.7/5 (856 download)

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Book Synopsis Signal Processing and Machine Learning for Brain-Machine Interfaces by : Toshihisa Tanaka

Download or read book Signal Processing and Machine Learning for Brain-Machine Interfaces written by Toshihisa Tanaka and published by Institution of Engineering and Technology. This book was released on 2018-09 with total page 355 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book introduces signal processing and machine learning techniques for Brain Machine Interfacing/Brain Computer Interfacing (BMI/BCI), and their practical and future applications in neuroscience, medicine, and rehabilitation. This is an emerging and challenging technology in engineering, computing, machine learning, neuroscience and medicine, and so the book will interest researchers, engineers, professionals and specialists from all of these areas who need to know more about cutting edge technologies in the fields.

Intelligent Systems and Signal Processing in Power Engineering

Author : Abhisek Ukil
Publisher : Springer Science & Business Media
ISBN 13 : 3540731709
Total Pages : 372 pages
Book Rating : 4.5/5 (47 download)

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Book Synopsis Intelligent Systems and Signal Processing in Power Engineering by : Abhisek Ukil

Download or read book Intelligent Systems and Signal Processing in Power Engineering written by Abhisek Ukil and published by Springer Science & Business Media. This book was released on 2007-09-23 with total page 372 pages. Available in PDF, EPUB and Kindle. Book excerpt: This highly experienced author sets out to build a bridge between two inter-disciplinary power engineering practices. The book looks into two major fields used in modern power systems: intelligent systems and the signal processing. The intelligent systems section comprises fuzzy logic, neural network and support vector machine. The author looks at relevant theories on the topics without assuming much particular background. Following the theoretical basics, he studies their applications in various problems in power engineering, like, load forecasting, phase balancing, or disturbance analysis.

Practical Guide for Biomedical Signals Analysis Using Machine Learning Techniques

Author : Abdulhamit Subasi
Publisher : Academic Press
ISBN 13 : 0128176733
Total Pages : 456 pages
Book Rating : 4.1/5 (281 download)

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Book Synopsis Practical Guide for Biomedical Signals Analysis Using Machine Learning Techniques by : Abdulhamit Subasi

Download or read book Practical Guide for Biomedical Signals Analysis Using Machine Learning Techniques written by Abdulhamit Subasi and published by Academic Press. This book was released on 2019-03-16 with total page 456 pages. Available in PDF, EPUB and Kindle. Book excerpt: Practical Guide for Biomedical Signals Analysis Using Machine Learning Techniques: A MATLAB Based Approach presents how machine learning and biomedical signal processing methods can be used in biomedical signal analysis. Different machine learning applications in biomedical signal analysis, including those for electrocardiogram, electroencephalogram and electromyogram are described in a practical and comprehensive way, helping readers with limited knowledge. Sections cover biomedical signals and machine learning techniques, biomedical signals, such as electroencephalogram (EEG), electromyogram (EMG) and electrocardiogram (ECG), different signal-processing techniques, signal de-noising, feature extraction and dimension reduction techniques, such as PCA, ICA, KPCA, MSPCA, entropy measures, and other statistical measures, and more. This book is a valuable source for bioinformaticians, medical doctors and other members of the biomedical field who need a cogent resource on the most recent and promising machine learning techniques for biomedical signals analysis. Provides comprehensive knowledge in the application of machine learning tools in biomedical signal analysis for medical diagnostics, brain computer interface and man/machine interaction Explains how to apply machine learning techniques to EEG, ECG and EMG signals Gives basic knowledge on predictive modeling in biomedical time series and advanced knowledge in machine learning for biomedical time series

Signals, Instrumentation, Control, And Machine Learning: An Integrative Introduction

Author : Joseph Bentsman
Publisher : World Scientific
ISBN 13 : 9811251886
Total Pages : 844 pages
Book Rating : 4.8/5 (112 download)

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Book Synopsis Signals, Instrumentation, Control, And Machine Learning: An Integrative Introduction by : Joseph Bentsman

Download or read book Signals, Instrumentation, Control, And Machine Learning: An Integrative Introduction written by Joseph Bentsman and published by World Scientific. This book was released on 2022-03-07 with total page 844 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book stems from a unique and a highly effective approach to introducing signal processing, instrumentation, diagnostics, filtering, control, system integration, and machine learning.It presents the interactive industrial grade software testbed of mold oscillator that captures the distortion induced by beam resonance and uses this testbed as a virtual lab to generate input-output data records that permit unravelling complex system behavior, enhancing signal processing, modeling, and simulation background, and testing controller designs.All topics are presented in a visually rich and mathematically well supported, but not analytically overburdened format. By incorporating software testbed into homework and project assignments, the narrative guides a reader in an easily followed step-by-step fashion towards finding the mold oscillator disturbance removal solution currently used in the actual steel production, while covering the key signal processing, control, system integration, and machine learning concepts.The presentation is extensively class-tested and refined though the six-year usage of the book material in a required engineering course at the University of Illinois at Urbana-Champaign.