Machine Intelligence And Signal Analysis

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Machine Intelligence and Signal Analysis

M. Tanveer,Ram Bilas Pachori
Machine Intelligence and Signal Analysis Book PDF

Author : M. Tanveer,Ram Bilas Pachori
Publisher : Springer
Page : 767 pages
File Size : 47,5 Mb
Release : 2018-08-07
Category : Technology & Engineering
ISBN : 9789811309236

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Machine Intelligence and Signal Analysis by M. Tanveer,Ram Bilas Pachori Pdf

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 Intelligence and Signal Analysis

M. Tanveer,Ram Bilas Pachori
Machine Intelligence and Signal Analysis Book PDF

Author : M. Tanveer,Ram Bilas Pachori
Publisher : Unknown
Page : 128 pages
File Size : 55,9 Mb
Release : 2019
Category : Artificial intelligence
ISBN : 9811309248

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Machine Intelligence and Signal Analysis by M. Tanveer,Ram Bilas Pachori Pdf

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 Intelligence Techniques for Data Analysis and Signal Processing

Dilip Singh Sisodia,Lalit Garg,Ram Bilas Pachori,M. Tanveer
Machine Intelligence Techniques for Data Analysis and Signal Processing Book PDF

Author : Dilip Singh Sisodia,Lalit Garg,Ram Bilas Pachori,M. Tanveer
Publisher : Springer Nature
Page : 879 pages
File Size : 50,9 Mb
Release : 2023-05-30
Category : Technology & Engineering
ISBN : 9789819900855

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Machine Intelligence Techniques for Data Analysis and Signal Processing by Dilip Singh Sisodia,Lalit Garg,Ram Bilas Pachori,M. Tanveer Pdf

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 Intelligence and Signal Processing

Sonali Agarwal,Shekhar Verma,Dharma P. Agrawal
Machine Intelligence and Signal Processing Book PDF

Author : Sonali Agarwal,Shekhar Verma,Dharma P. Agrawal
Publisher : Springer Nature
Page : 466 pages
File Size : 49,7 Mb
Release : 2020-02-25
Category : Technology & Engineering
ISBN : 9789811513664

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Machine Intelligence and Signal Processing by Sonali Agarwal,Shekhar Verma,Dharma P. Agrawal Pdf

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).

Machine Learning in Signal Processing

Sudeep Tanwar,Anand Nayyar,Rudra Rameshwar
Machine Learning in Signal Processing Book PDF

Author : Sudeep Tanwar,Anand Nayyar,Rudra Rameshwar
Publisher : CRC Press
Page : 488 pages
File Size : 49,9 Mb
Release : 2021-12-10
Category : Technology & Engineering
ISBN : 9781000487817

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Machine Learning in Signal Processing by Sudeep Tanwar,Anand Nayyar,Rudra Rameshwar Pdf

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.

Advanced Machine Intelligence and Signal Processing

Deepak Gupta,Koj Sambyo,Mukesh Prasad,Sonali Agarwal
Advanced Machine Intelligence and Signal Processing Book PDF

Author : Deepak Gupta,Koj Sambyo,Mukesh Prasad,Sonali Agarwal
Publisher : Springer Nature
Page : 859 pages
File Size : 47,7 Mb
Release : 2022-06-25
Category : Technology & Engineering
ISBN : 9789811908408

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Advanced Machine Intelligence and Signal Processing by Deepak Gupta,Koj Sambyo,Mukesh Prasad,Sonali Agarwal Pdf

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).

Machine Learning in Signal Processing

Sudeep Tanwar,Anand Nayyar,Rudra Rameshwar
Machine Learning in Signal Processing Book PDF

Author : Sudeep Tanwar,Anand Nayyar,Rudra Rameshwar
Publisher : CRC Press
Page : 388 pages
File Size : 41,5 Mb
Release : 2021-12-10
Category : Technology & Engineering
ISBN : 9781000487794

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Machine Learning in Signal Processing by Sudeep Tanwar,Anand Nayyar,Rudra Rameshwar Pdf

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 Learning in Bio-Signal Analysis and Diagnostic Imaging

Nilanjan Dey,Surekha Borra,Amira S. Ashour,Fuqian Shi
Machine Learning in Bio Signal Analysis and Diagnostic Imaging Book PDF

Author : Nilanjan Dey,Surekha Borra,Amira S. Ashour,Fuqian Shi
Publisher : Academic Press
Page : 345 pages
File Size : 44,9 Mb
Release : 2018-11-30
Category : Science
ISBN : 9780128160879

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Machine Learning in Bio-Signal Analysis and Diagnostic Imaging by Nilanjan Dey,Surekha Borra,Amira S. Ashour,Fuqian Shi Pdf

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

Signal Processing and Machine Learning with Applications

Michael M. Richter,Sheuli Paul,Veton Këpuska,Marius Silaghi
Signal Processing and Machine Learning with Applications Book PDF

Author : Michael M. Richter,Sheuli Paul,Veton Këpuska,Marius Silaghi
Publisher : Springer
Page : 0 pages
File Size : 51,5 Mb
Release : 2022-10-01
Category : Computers
ISBN : 3319453718

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Signal Processing and Machine Learning with Applications by Michael M. Richter,Sheuli Paul,Veton Këpuska,Marius Silaghi Pdf

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 Intelligence and Signal Processing

Richa Singh,Mayank Vatsa,Angshul Majumdar,Ajay Kumar
Machine Intelligence and Signal Processing Book PDF

Author : Richa Singh,Mayank Vatsa,Angshul Majumdar,Ajay Kumar
Publisher : Springer
Page : 163 pages
File Size : 44,7 Mb
Release : 2015-10-01
Category : Technology & Engineering
ISBN : 9788132226253

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Machine Intelligence and Signal Processing by Richa Singh,Mayank Vatsa,Angshul Majumdar,Ajay Kumar Pdf

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 Methods for Signal, Image and Speech Processing

M.A. Jabbar,MVV Prasad Kantipudi,Sheng-Lung Peng,Mamun Bin Ibne Reaz,Ana Maria Madureira
Machine Learning Methods for Signal Image and Speech Processing Book PDF

Author : M.A. Jabbar,MVV Prasad Kantipudi,Sheng-Lung Peng,Mamun Bin Ibne Reaz,Ana Maria Madureira
Publisher : CRC Press
Page : 257 pages
File Size : 52,8 Mb
Release : 2022-09-01
Category : Computers
ISBN : 9781000794748

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Machine Learning Methods for Signal, Image and Speech Processing by M.A. Jabbar,MVV Prasad Kantipudi,Sheng-Lung Peng,Mamun Bin Ibne Reaz,Ana Maria Madureira Pdf

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.

Practical Guide for Biomedical Signals Analysis Using Machine Learning Techniques

Abdulhamit Subasi
Practical Guide for Biomedical Signals Analysis Using Machine Learning Techniques Book PDF

Author : Abdulhamit Subasi
Publisher : Academic Press
Page : 456 pages
File Size : 55,6 Mb
Release : 2019-03-16
Category : Business & Economics
ISBN : 9780128176733

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Practical Guide for Biomedical Signals Analysis Using Machine Learning Techniques by Abdulhamit Subasi Pdf

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

Financial Signal Processing and Machine Learning

Ali N. Akansu,Sanjeev R. Kulkarni,Dmitry M. Malioutov
Financial Signal Processing and Machine Learning Book PDF

Author : Ali N. Akansu,Sanjeev R. Kulkarni,Dmitry M. Malioutov
Publisher : John Wiley & Sons
Page : 312 pages
File Size : 43,8 Mb
Release : 2016-04-21
Category : Technology & Engineering
ISBN : 9781118745632

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Financial Signal Processing and Machine Learning by Ali N. Akansu,Sanjeev R. Kulkarni,Dmitry M. Malioutov Pdf

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.

Biomedical Signal Processing and Artificial Intelligence in Healthcare

Walid A. Zgallai
Biomedical Signal Processing and Artificial Intelligence in Healthcare Book PDF

Author : Walid A. Zgallai
Publisher : Academic Press
Page : 270 pages
File Size : 49,7 Mb
Release : 2020-07-29
Category : Technology & Engineering
ISBN : 9780128189474

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Biomedical Signal Processing and Artificial Intelligence in Healthcare by Walid A. Zgallai Pdf

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

Machine Learning for Signal Processing

Max A. Little
Machine Learning for Signal Processing Book PDF

Author : Max A. Little
Publisher : Oxford University Press, USA
Page : 378 pages
File Size : 48,9 Mb
Release : 2019
Category : Computers
ISBN : 9780198714934

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Machine Learning for Signal Processing by Max A. Little Pdf

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.