Intelligent Signal Processing
Intelligent Signal Processing

Author: Simon Haykin

Publisher: Wiley-IEEE Press

Published: 2001-01-15

Total Pages: 610

ISBN-13:

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"IEEE Press is proud to present the first selected reprint volume devoted to the new field of intelligent signal processing (ISP). ISP differs fundamentally from the classical approach to statistical signal processing in that the input-output behavior of a complex system is modeled by using "intelligent" or "model-free" techniques, rather than relying on the shortcomings of a mathematical model. Information is extracted from incoming signal and noise data, making few assumptions about the statistical structure of signals and their environment. Intelligent Signal Processing explores how ISP tools address the problems of practical neural systems, new signal data, and blind fuzzy approximators. The editors have compiled 20 articles written by prominent researchers covering 15 diverse, practical applications of this nascent topic, exposing the reader to the signal processing power of learning and adaptive systems. This essential reference is intended for researchers, professional engineers, and scientists working in statistical signal processing and its applications in various fields such as humanistic intelligence, stochastic resonance, financial markets, optimization, pattern recognition, signal detection, speech processing, and sensor fusion. Intelligent Signal Processing is also invaluable for graduate students and academics with a background in computer science, computer engineering, or electrical engineering. About the Editors Simon Haykin is the founding director of the Communications Research Laboratory at McMaster University, Hamilton, Ontario, Canada, where he serves as university professor. His research interests include nonlinear dynamics, neural networks and adaptive filters and their applications in radar and communications systems. Dr. Haykin is the editor for a series of books on "Adaptive and Learning Systems for Signal Processing, Communications and Control" (Publisher) and is both an IEEE Fellow and Fellow of the Royal Society of Canada. Bart Kosko is a past director of the University of Southern California's (USC) Signal and Image Processing Institute. He has authored several books, including Neural Networks and Fuzzy Systems, Neural Networks for Signal Processing (Publisher, copyright date) and Fuzzy Thinking (Publisher, copyright date), as well as the novel Nanotime (Publisher, copyright date). Dr. Kosko is an elected governor of the International Neural Network Society and has chaired many neural and fuzzy system conferences. Currently, he is associate professor of electrical engineering at USC."

Intelligent Speech Signal Processing
Intelligent Speech Signal Processing

Author: Nilanjan Dey

Publisher: Academic Press

Published: 2019-04-02

Total Pages: 210

ISBN-13: 0128181303

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Intelligent Speech Signal Processing investigates the utilization of speech analytics across several systems and real-world activities, including sharing data analytics, creating collaboration networks between several participants, and implementing video-conferencing in different application areas. Chapters focus on the latest applications of speech data analysis and management tools across different recording systems. The book emphasizes the multidisciplinary nature of the field, presenting different applications and challenges with extensive studies on the design, development and management of intelligent systems, neural networks and related machine learning techniques for speech signal processing.

Signal Processing for Intelligent Sensor Systems with MATLAB®
Signal Processing for Intelligent Sensor Systems with MATLAB®

Author: David C. Swanson

Publisher: CRC Press

Published: 2011-07-21

Total Pages: 684

ISBN-13: 1439879508

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Signal Processing for Intelligent Sensors with MATLAB®, Second Edition once again presents the key topics and salient information required for sensor design and application. Organized to make it accessible to engineers in school as well as those practicing in the field, this reference explores a broad array of subjects and is divided into sections: Fundamentals of Digital Signal Processing, Frequency Domain Processing, Adaptive System Identification and Filtering, Wavenumber Sensor Systems, and Signal Processing Applications. Taking an informal, application-based approach and using a tone that is more engineer-to-engineer than professor-to-student, this revamped second edition enhances many of the features that made the original so popular. This includes retention of key algorithms and development methodologies and applications, which are creatively grouped in a way that differs from most comparable texts, to optimize their use. New for the Second Edition: Inclusion of more solved problems Web access to a large collection of MATLAB® scripts used to support data graphs presented throughout the book Additional coverage of more audio engineering, transducers, and sensor networking technology A new chapter on Digital Audio processing reflects a growing interest in digital surround sound (5.1 audio) techniques for entertainment, home theaters, and virtual reality systems New sections on sensor networking, use of meta-data architectures using XML, and agent-based automated data mining and control Serving dual roles as both a learning resource and a field reference on sensor system networks, this book progressively reveals digestible nuggets of critical information to help readers quickly master presented algorithms and adapt them to meet their requirements. It illustrates the current trend toward agile development of web services for wide area sensor networking and intelligent processing in the sensor system networks that are employed in homeland security, business, and environmental and demographic information systems.

Neural Networks for Intelligent Signal Processing
Neural Networks for Intelligent Signal Processing

Author: Anthony Zaknich

Publisher: World Scientific

Published: 2003

Total Pages: 510

ISBN-13: 9812383050

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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.

Intelligent Systems and Signal Processing in Power Engineering
Intelligent Systems and Signal Processing in Power Engineering

Author: Abhisek Ukil

Publisher: Springer Science & Business Media

Published: 2007-09-23

Total Pages: 384

ISBN-13: 3540731709

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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.

Intelligent Sensor Networks
Intelligent Sensor Networks

Author: Fei Hu

Publisher: CRC Press

Published: 2012-12-15

Total Pages: 676

ISBN-13: 1439892814

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Although governments worldwide have invested significantly in intelligent sensor network research and applications, few books cover intelligent sensor networks from a machine learning and signal processing perspective. Filling this void, Intelligent Sensor Networks: The Integration of Sensor Networks, Signal Processing and Machine Learning focuses on the close integration of sensing, networking, and smart signal processing via machine learning. Based on the world-class research of award-winning authors, the book provides a firm grounding in the fundamentals of intelligent sensor networks, including compressive sensing and sampling, distributed signal processing, and intelligent signal learning. Presenting recent research results of world-renowned sensing experts, the book is organized into three parts: Machine Learning—describes the application of machine learning and other AI principles in sensor network intelligence—covering smart sensor/transducer architecture and data representation for intelligent sensors Signal Processing—considers the optimization of sensor network performance based on digital signal processing techniques—including cross-layer integration of routing and application-specific signal processing as well as on-board image processing in wireless multimedia sensor networks for intelligent transportation systems Networking—focuses on network protocol design in order to achieve an intelligent sensor networking—covering energy-efficient opportunistic routing protocols for sensor networking and multi-agent-driven wireless sensor cooperation Maintaining a focus on "intelligent" designs, the book details signal processing principles in sensor networks. It elaborates on critical platforms for intelligent sensor networks and illustrates key applications—including target tracking, object identification, and structural health monitoring. It also includes a paradigm for validating the extent of spatiotemporal associations among data sources to enhance data cleaning in sensor networks, a sensor stream reduction application, and also considers the use of Kalman filters for attack detection in a water system sensor network that consists of water level sensors and velocity sensors.

Advances in Signal Processing and Intelligent Recognition Systems
Advances in Signal Processing and Intelligent Recognition Systems

Author: Sabu M. Thampi

Publisher: Springer Nature

Published: 2020-04-30

Total Pages: 414

ISBN-13: 9811548285

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This book constitutes the refereed proceedings of the 5th International Symposium on Advances in Signal Processing and Intelligent Recognition Systems, SIRS 2019, held in Trivandrum, India, in December 2019. The 19 revised full papers and 8 revised short papers presented were carefully reviewed and selected from 63 submissions. The papers cover wide research fields including information retrieval, human-computer interaction (HCI), information extraction, speech recognition.

Advances in Signal Processing and Intelligent Recognition Systems
Advances in Signal Processing and Intelligent Recognition Systems

Author: Sabu M. Thampi

Publisher: Springer Science & Business Media

Published: 2014-02-14

Total Pages: 607

ISBN-13: 3319049607

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This edited volume contains a selection of refereed and revised papers originally presented at the International Symposium on Signal Processing and Intelligent Recognition Systems (SIRS-2014), March 13-15, 2014, Trivandrum, India. The program committee received 134 submissions from 11 countries. Each paper was peer reviewed by at least three or more independent referees of the program committee and the 52 papers were finally selected. The papers offer stimulating insights into Pattern Recognition, Machine Learning and Knowledge-Based Systems; Signal and Speech Processing; Image and Video Processing; Mobile Computing and Applications and Computer Vision. The book is directed to the researchers and scientists engaged in various field of signal processing and related areas.

Advances in Intelligent Signal Processing and Data Mining
Advances in Intelligent Signal Processing and Data Mining

Author: Petia Georgieva

Publisher: Springer

Published: 2012-07-27

Total Pages: 359

ISBN-13: 3642286968

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The book presents some of the most efficient statistical and deterministic methods for information processing and applications in order to extract targeted information and find hidden patterns. The techniques presented range from Bayesian approaches and their variations such as sequential Monte Carlo methods, Markov Chain Monte Carlo filters, Rao Blackwellization, to the biologically inspired paradigm of Neural Networks and decomposition techniques such as Empirical Mode Decomposition, Independent Component Analysis and Singular Spectrum Analysis. The book is directed to the research students, professors, researchers and practitioners interested in exploring the advanced techniques in intelligent signal processing and data mining paradigms.

Intelligent Computing for Interactive System Design
Intelligent Computing for Interactive System Design

Author: Parisa Eslambolchilar

Publisher: ACM Books

Published: 2021-02-25

Total Pages: 472

ISBN-13: 9781450390262

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Intelligent Computing for Interactive System Design provides a comprehensive resource on what has become the dominant paradigm in designing novel interaction methods, involving gestures, speech, text, touch and brain-controlled interaction, embedded in innovative and emerging human-computer interfaces. These interfaces support ubiquitous interaction with applications and services running on smartphones, wearables, in-vehicle systems, virtual and augmented reality, robotic systems, the Internet of Things (IoT), and many other domains that are now highly competitive, both in commercial and in research contexts. This book presents the crucial theoretical foundations needed by any student, researcher, or practitioner working on novel interface design, with chapters on statistical methods, digital signal processing (DSP), and machine learning (ML). These foundations are followed by chapters that discuss case studies on smart cities, brain-computer interfaces, probabilistic mobile text entry, secure gestures, personal context from mobile phones, adaptive touch interfaces, and automotive user interfaces. The case studies chapters also highlight an in-depth look at the practical application of DSP and ML methods used for processing of touch, gesture, biometric, or embedded sensor inputs. A common theme throughout the case studies is ubiquitous support for humans in their daily professional or personal activities. In addition, the book provides walk-through examples of different DSP and ML techniques and their use in interactive systems. Common terms are defined, and information on practical resources is provided (e.g., software tools, data resources) for hands-on project work to develop and evaluate multimodal and multi-sensor systems. In a series of in-chapter commentary boxes, an expert on the legal and ethical issues explores the emergent deep concerns of the professional community, on how DSP and ML should be adopted and used in socially appropriate ways, to most effectively advance human performance during ubiquitous interaction with omnipresent computers. This carefully edited collection is written by international experts and pioneers in the fields of DSP and ML. It provides a textbook for students and a reference and technology roadmap for developers and professionals working on interaction design on emerging platforms.