Artificial Intelligence Enabled Signal Processing Based Models For Neural Information Processing

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Artificial Intelligence Enabled Signal Processing based Models for Neural Information Processing

Rajesh Kumar Tripathy,Ram Bilas Pachori
Artificial Intelligence Enabled Signal Processing based Models for Neural Information Processing Book PDF

Author : Rajesh Kumar Tripathy,Ram Bilas Pachori
Publisher : CRC Press
Page : 227 pages
File Size : 40,9 Mb
Release : 2024-06-06
Category : Technology & Engineering
ISBN : 9781040028773

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Artificial Intelligence Enabled Signal Processing based Models for Neural Information Processing by Rajesh Kumar Tripathy,Ram Bilas Pachori Pdf

The book provides details regarding the application of various signal processing and artificial intelligence-based methods for electroencephalography data analysis. It will help readers in understanding the use of electroencephalography signals for different neural information processing and cognitive neuroscience applications. The book: Covers topics related to the application of signal processing and machine learning-based techniques for the analysis and classification of electroencephalography signals Presents automated methods for detection of neurological disorders and other applications such as cognitive task recognition, and brain-computer interface Highlights the latest machine learning and deep learning methods for neural signal processing Discusses mathematical details for the signal processing and machine learning algorithms applied for electroencephalography data analysis Showcases the detection of dementia from electroencephalography signals using signal processing and machine learning-based techniques It is primarily written for senior undergraduates, graduate students, and researchers in the fields of electrical engineering, electronics and communications engineering, and biomedical engineering.

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 : 54,8 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.

Artificial Neural Networks as Models of Neural Information Processing

Marcel van Gerven,Sander Bohte
Artificial Neural Networks as Models of Neural Information Processing Book PDF

Author : Marcel van Gerven,Sander Bohte
Publisher : Frontiers Media SA
Page : 220 pages
File Size : 40,7 Mb
Release : 2018-02-01
Category : Electronic
ISBN : 9782889454013

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Artificial Neural Networks as Models of Neural Information Processing by Marcel van Gerven,Sander Bohte Pdf

Modern neural networks gave rise to major breakthroughs in several research areas. In neuroscience, we are witnessing a reappraisal of neural network theory and its relevance for understanding information processing in biological systems. The research presented in this book provides various perspectives on the use of artificial neural networks as models of neural information processing. We consider the biological plausibility of neural networks, performance improvements, spiking neural networks and the use of neural networks for understanding brain function.

Neural Networks in a Softcomputing Framework

Ke-Lin Du,M.N.S. Swamy
Neural Networks in a Softcomputing Framework Book PDF

Author : Ke-Lin Du,M.N.S. Swamy
Publisher : Springer Science & Business Media
Page : 566 pages
File Size : 42,9 Mb
Release : 2006-08-02
Category : Technology & Engineering
ISBN : 9781846283031

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Neural Networks in a Softcomputing Framework by Ke-Lin Du,M.N.S. Swamy Pdf

This concise but comprehensive textbook reviews the most popular neural-network methods and their associated techniques. Each chapter provides state-of-the-art descriptions of important major research results of the respective neural-network methods. A range of relevant computational intelligence topics, such as fuzzy logic and evolutionary algorithms – powerful tools for neural-network learning – are introduced. The systematic survey of neural-network models and exhaustive references list will point readers toward topics for future research. The algorithms outlined also make this textbook a valuable reference for scientists and practitioners working in pattern recognition, signal processing, speech and image processing, data analysis and artificial intelligence.

Machine Learning Algorithms for Signal and Image Processing

Suman Lata Tripathi,Deepika Ghai,Sobhit Saxena,Manash Chanda,Mamoun Alazab
Machine Learning Algorithms for Signal and Image Processing Book PDF

Author : Suman Lata Tripathi,Deepika Ghai,Sobhit Saxena,Manash Chanda,Mamoun Alazab
Publisher : John Wiley & Sons
Page : 516 pages
File Size : 44,9 Mb
Release : 2022-12-01
Category : Technology & Engineering
ISBN : 9781119861829

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Machine Learning Algorithms for Signal and Image Processing by Suman Lata Tripathi,Deepika Ghai,Sobhit Saxena,Manash Chanda,Mamoun Alazab Pdf

Enables readers to understand the fundamental concepts of machine and deep learning techniques with interactive, real-life applications within signal and image processing Machine Learning Algorithms for Signal and Image Processing aids the reader in designing and developing real-world applications using advances in machine learning to aid and enhance speech signal processing, image processing, computer vision, biomedical signal processing, adaptive filtering, and text processing. It includes signal processing techniques applied for pre-processing, feature extraction, source separation, or data decompositions to achieve machine learning tasks. Written by well-qualified authors and contributed to by a team of experts within the field, the work covers a wide range of important topics, such as: Speech recognition, image reconstruction, object classification and detection, and text processing Healthcare monitoring, biomedical systems, and green energy How various machine and deep learning techniques can improve accuracy, precision rate recall rate, and processing time Real applications and examples, including smart sign language recognition, fake news detection in social media, structural damage prediction, and epileptic seizure detection Professionals within the field of signal and image processing seeking to adapt their work further will find immense value in this easy-to-understand yet extremely comprehensive reference work. It is also a worthy resource for students and researchers in related fields who are looking to thoroughly understand the historical and recent developments that have been made in the field.

Neural Networks for Intelligent Signal Processing

Anthony Zaknich
Neural Networks for Intelligent Signal Processing Book PDF

Author : Anthony Zaknich
Publisher : World Scientific
Page : 510 pages
File Size : 52,8 Mb
Release : 2003
Category : Computers
ISBN : 9789812796851

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Neural Networks for Intelligent Signal Processing by Anthony Zaknich Pdf

This book provides a thorough theoretical and practical introduction to the application of neural networks to pattern recognition and intelligent signal processing. It has been tested on students, unfamiliar with neural networks, who were able to pick up enough details to successfully complete their masters or final year undergraduate projects. The text also presents a comprehensive treatment of a class of neural networks called common bandwidth spherical basis function NNs, including the probabilistic NN, the modified probabilistic NN and the general regression NN. Contents: A Brief Historical Overview; Basic Concepts; ANN Performance Evaluation; Basic Pattern Recognition Principles; ADALINES, Adaptive Filters, and Multi-Layer Perceptrons; Probabilistic Neural Network Classifier; General Regression Neural Network; The Modified Probabilistic Neural Network; Advanced MPNN Developments; Neural Networks Similar to the Common Bandwidth Spherical Basis Function Regression ANNs; Unsupervised Learning Neural Networks; Other Neural Network Models; Statistical Learning Theory; Application to Intelligent Signal Processing; Application to Intelligent Control. Readership: Students and professionals in computer science and engineering.

New Advances in Intelligent Signal Processing

Antonio Ruano,Annamária R. Várkonyi-Kóczy
New Advances in Intelligent Signal Processing Book PDF

Author : Antonio Ruano,Annamária R. Várkonyi-Kóczy
Publisher : Springer Science & Business Media
Page : 260 pages
File Size : 46,5 Mb
Release : 2011-09-07
Category : Mathematics
ISBN : 9783642117381

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New Advances in Intelligent Signal Processing by Antonio Ruano,Annamária R. Várkonyi-Kóczy Pdf

The current volume “New Advances in Intelligent Signal Processing” contains extended works based on a careful selection of papers presented originally at the jubilee sixth IEEE International Symposium on Intelligent Signal Processing (WISP’2009), held in Budapest Hungary, August 26-28, 2009 - celebrating the 10 years anniversary of the WISP event series. The present book does not intent to be an overall survey on the fields of interest of the area, but tries to find topics which represent new, hot, and challenging problems. The book begins with papers investigating selected problems of Modeling, Identification, and Clustering such as fuzzy random variables, evolutionary multi-objective neural network models, a structural learning model of neural networks within a Boltzmann machine, a robust DNA-based clustering techniques, and the advances of combining multi-criteria analysis of signals and pattern recognition using machine learning principles. In the second part of the book Image Processing is treated. The carefully edited chapters deal with fuzzy relation based image enhancement, image contrast control technique based on the application of Łukasiewicz algebra operators, low complexity situational models of image quality improvement, flexible representation of map images to quantum computers, and object recognition in images. The last chapter presents an image processing application for elderly care, performing real-time 3D tracking based on a new evaluative multi-modal algorithm.

Cognitive Systems and Signal Processing

Fuchun Sun,Huaping Liu,Dewen Hu
Cognitive Systems and Signal Processing Book PDF

Author : Fuchun Sun,Huaping Liu,Dewen Hu
Publisher : Springer
Page : 534 pages
File Size : 46,6 Mb
Release : 2019-04-26
Category : Computers
ISBN : 9789811379864

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Cognitive Systems and Signal Processing by Fuchun Sun,Huaping Liu,Dewen Hu Pdf

This two-volume set (CCIS 1005 and CCIS 1006) constitutes the refereed proceedings of the 4th International Conference on Cognitive Systems and Signal Processing, ICCSIP2018, held in Beijing, China, in November and December 2018. The 96 revised full papers presented were carefully reviewed and selected from 169 submissions. The papers are organized in topical sections on vision and image; algorithms; robotics; human-computer interaction; deep learning; information processing and automatic driving.

Neural Information Processing

Sabri Arik,Tingwen Huang,Weng Kin Lai,Qingshan Liu
Neural Information Processing Book PDF

Author : Sabri Arik,Tingwen Huang,Weng Kin Lai,Qingshan Liu
Publisher : Springer
Page : 702 pages
File Size : 47,5 Mb
Release : 2015-11-17
Category : Computers
ISBN : 9783319265612

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Neural Information Processing by Sabri Arik,Tingwen Huang,Weng Kin Lai,Qingshan Liu Pdf

The four volume set LNCS 9489, LNCS 9490, LNCS 9491, and LNCS 9492 constitutes the proceedings of the 22nd International Conference on Neural Information Processing, ICONIP 2015, held in Istanbul, Turkey, in November 2015. The 231 full papers presented were carefully reviewed and selected from 375 submissions. The 4 volumes represent topical sections containing articles on Learning Algorithms and Classification Systems; Artificial Intelligence and Neural Networks: Theory, Design, and Applications; Image and Signal Processing; and Intelligent Social Networks.

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 : 51,9 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 and Deep Learning Algorithms and Applications

Uday Shankar Shanthamallu,Andreas Spanias
Machine and Deep Learning Algorithms and Applications Book PDF

Author : Uday Shankar Shanthamallu,Andreas Spanias
Publisher : Morgan & Claypool Publishers
Page : 123 pages
File Size : 44,8 Mb
Release : 2021-12-22
Category : Technology & Engineering
ISBN : 9781636392660

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Machine and Deep Learning Algorithms and Applications by Uday Shankar Shanthamallu,Andreas Spanias Pdf

This book introduces basic machine learning concepts and applications for a broad audience that includes students, faculty, and industry practitioners. We begin by describing how machine learning provides capabilities to computers and embedded systems to learn from data. A typical machine learning algorithm involves training, and generally the performance of a machine learning model improves with more training data. Deep learning is a sub-area of machine learning that involves extensive use of layers of artificial neural networks typically trained on massive amounts of data. Machine and deep learning methods are often used in contemporary data science tasks to address the growing data sets and detect, cluster, and classify data patterns. Although machine learning commercial interest has grown relatively recently, the roots of machine learning go back to decades ago. We note that nearly all organizations, including industry, government, defense, and health, are using machine learning to address a variety of needs and applications. The machine learning paradigms presented can be broadly divided into the following three categories: supervised learning, unsupervised learning, and semi-supervised learning. Supervised learning algorithms focus on learning a mapping function, and they are trained with supervision on labeled data. Supervised learning is further sub-divided into classification and regression algorithms. Unsupervised learning typically does not have access to ground truth, and often the goal is to learn or uncover the hidden pattern in the data. Through semi-supervised learning, one can effectively utilize a large volume of unlabeled data and a limited amount of labeled data to improve machine learning model performances. Deep learning and neural networks are also covered in this book. Deep neural networks have attracted a lot of interest during the last ten years due to the availability of graphics processing units (GPU) computational power, big data, and new software platforms. They have strong capabilities in terms of learning complex mapping functions for different types of data. We organize the book as follows. The book starts by introducing concepts in supervised, unsupervised, and semi-supervised learning. Several algorithms and their inner workings are presented within these three categories. We then continue with a brief introduction to artificial neural network algorithms and their properties. In addition, we cover an array of applications and provide extensive bibliography. The book ends with a summary of the key machine learning concepts.

Computer Engineering And Artificial Intelligence 2

Khashayar Sharbati,Seyede Tahere Hoseini,Golestan Rasa,Sanaz Moazzami Goudarzi,Seyedhamid Hoseini,Parsa ForouzeshFar,Mohamad Samaei
Computer Engineering And Artificial Intelligence 2 Book PDF

Author : Khashayar Sharbati,Seyede Tahere Hoseini,Golestan Rasa,Sanaz Moazzami Goudarzi,Seyedhamid Hoseini,Parsa ForouzeshFar,Mohamad Samaei
Publisher : Nobel Science
Page : 78 pages
File Size : 43,8 Mb
Release : 2024-06-11
Category : Computers
ISBN : 8210379456XXX

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Computer Engineering And Artificial Intelligence 2 by Khashayar Sharbati,Seyede Tahere Hoseini,Golestan Rasa,Sanaz Moazzami Goudarzi,Seyedhamid Hoseini,Parsa ForouzeshFar,Mohamad Samaei Pdf

Chapter1: Artificial intelligence in medicine Chapter2: Microprocessor Chapter3: Digital signal processor Chapter4: Microcontroller Chapter5: Embedded processor

Neural Information Processing

Sabri Arik,Tingwen Huang,Weng Kin Lai,Qingshan Liu
Neural Information Processing Book PDF

Author : Sabri Arik,Tingwen Huang,Weng Kin Lai,Qingshan Liu
Publisher : Springer
Page : 710 pages
File Size : 54,8 Mb
Release : 2015-12-08
Category : Computers
ISBN : 9783319265551

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Neural Information Processing by Sabri Arik,Tingwen Huang,Weng Kin Lai,Qingshan Liu Pdf

The four volume set LNCS 9489, LNCS 9490, LNCS 9491, and LNCS 9492 constitutes the proceedings of the 22nd International Conference on Neural Information Processing, ICONIP 2015, held in Istanbul, Turkey, in November 2015. The 231 full papers presented were carefully reviewed and selected from 375 submissions. The 4 volumes represent topical sections containing articles on Learning Algorithms and Classification Systems; Artificial Intelligence and Neural Networks: Theory, Design, and Applications; Image and Signal Processing; and Intelligent Social Networks.

Neural Advances in Processing Nonlinear Dynamic Signals

Anna Esposito,Marcos Faundez-Zanuy,Francesco Carlo Morabito,Eros Pasero
Neural Advances in Processing Nonlinear Dynamic Signals Book PDF

Author : Anna Esposito,Marcos Faundez-Zanuy,Francesco Carlo Morabito,Eros Pasero
Publisher : Springer
Page : 318 pages
File Size : 50,9 Mb
Release : 2018-07-21
Category : Technology & Engineering
ISBN : 9783319950983

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Neural Advances in Processing Nonlinear Dynamic Signals by Anna Esposito,Marcos Faundez-Zanuy,Francesco Carlo Morabito,Eros Pasero Pdf

This book proposes neural networks algorithms and advanced machine learning techniques for processing nonlinear dynamic signals such as audio, speech, financial signals, feedback loops, waveform generation, filtering, equalization, signals from arrays of sensors, and perturbations in the automatic control of industrial production processes. It also discusses the drastic changes in financial, economic, and work processes that are currently being experienced by the computational and engineering sciences community. Addresses key aspects, such as the integration of neural algorithms and procedures for the recognition, the analysis and detection of dynamic complex structures and the implementation of systems for discovering patterns in data, the book highlights the commonalities between computational intelligence (CI) and information and communications technologies (ICT) to promote transversal skills and sophisticated processing techniques. This book is a valuable resource for a. The academic research community b. The ICT market c. PhD students and early stage researchers d. Companies, research institutes e. Representatives from industry and standardization bodies

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 : 40,7 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.