Download or read book Cellular Neural Networks and Visual Computing written by Leon O. Chua and published by Cambridge University Press. This book was released on 2002-05-30 with total page 412 pages. Available in PDF, EPUB and Kindle. Book excerpt: Cellular Nonlinear/neural Network (CNN) technology is both a revolutionary concept and an experimentally proven new computing paradigm. Analogic cellular computers based on CNNs are set to change the way analog signals are processed and are paving the way to an analog computing industry. This unique undergraduate level textbook includes many examples and exercises, including CNN simulator and development software accessible via the Internet. It is an ideal introduction to CNNs and analogic cellular computing for students, researchers and engineers from a wide range of disciplines. Although its prime focus is on visual computing, the concepts and techniques described in the book will be of great interest to those working in other areas of research including modeling of biological, chemical and physical processes. Leon Chua, co-inventor of the CNN, and Tamás Roska are both highly respected pioneers in the field.
Download or read book Cellular Neural Networks and Visual Computing written by Leon O. Chua and published by . This book was released on 2003-08-01 with total page 408 pages. Available in PDF, EPUB and Kindle. Book excerpt: Cellular Nonlinear/neural Network (CNN) technology is both a revolutionary concept and an experimentally proven new computing paradigm. Analogic cellular computers based on CNNs are set to change the way analog signals are processed and are paving the way to an entire new analog computing industry. This unique undergraduate level textbook includes many examples and exercises, including CNN simulator and development software accessible via the Internet. It is an ideal introduction to CNNs and analogic cellular computing for students, researchers and engineers from a wide range of disciplines. Although its prime focus is on visual computing, the concepts and techniques described in the book will be of great interest to those working in other areas of research including modeling of biological, chemical and physical processes. Leon Chua, co-inventor of the CNN, and Tamás Roska are both highly respected pioneers in the field.
Download or read book Convolutional Neural Networks in Visual Computing written by Ragav Venkatesan and published by CRC Press. This book was released on 2017-10-23 with total page 204 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book covers the fundamentals in designing and deploying techniques using deep architectures. It is intended to serve as a beginner's guide to engineers or students who want to have a quick start on learning and/or building deep learning systems. This book provides a good theoretical and practical understanding and a complete toolkit of basic information and knowledge required to understand and build convolutional neural networks (CNN) from scratch. The book focuses explicitly on convolutional neural networks, filtering out other material that co-occur in many deep learning books on CNN topics.
Download or read book Thinking in Complexity written by Klaus Mainzer and published by Springer Science & Business Media. This book was released on 2007-09-07 with total page 491 pages. Available in PDF, EPUB and Kindle. Book excerpt: This new edition also treats smart materials and artificial life. A new chapter on information and computational dynamics takes up many recent discussions in the community.
Download or read book Cellular Neural Networks and Visual Computing written by Leon O. Chua and published by Cambridge University Press. This book was released on 2005-08-22 with total page 412 pages. Available in PDF, EPUB and Kindle. Book excerpt: Cellular Nonlinear/Neural Network (CNN) technology is both a revolutionary concept and an experimentally proven new computing paradigm. Analogic cellular computers based on CNNs are set to change the way analog signals are processed. This unique undergraduate level textbook includes many examples and exercises, including CNN simulator and development software accessible via the Internet. It is an ideal introduction to CNNs and analogic cellular computing for students, researchers and engineers from a wide range of disciplines. Leon Chua, co-inventor of the CNN, and Tamàs Roska are both highly respected pioneers in the field.
Download or read book Cellular Nanoscale Sensory Wave Computing written by Chagaan Baatar and published by Springer Science & Business Media. This book was released on 2010-03-14 with total page 252 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is loosely based on a Multidisciplinary University Research Initiative (MURI) project and a few supplemental projects sponsored by the Of?ce of Naval Research (ONR) during the time frame of 2004–2009. The initial technical scope and vision of the MURI project was formulated by Drs. Larry Cooper and Joel Davis, both program of?cers at ONR at the time. The unifying theme of this MURI project and its companionefforts is the concept of cellular nonlinear/neuralnetwork (CNN) technology and its various extensions and chip implementations, including nanoscale sensors and the broadening ?eld of cellular wave computing. In recent years, CNN-based vision system drew much attention from vision scientists to device technologists and computer architects. Due to its early - plementation in a two-dimensional (2D) topography, it found success in early vision technologyapplications, such as focal-plane arrays, locally adaptable sensor/ processor integration, resulting in extremely high frame rates of 10,000 frames per second. More recently it drew increasing attention from computer architects, due to its intrinsic local interconnect architecture and parallel processing paradigm. As a result, a few spin-off companies have already been successful in bringing cel- lar wave computing and CNN technology to the market. This book aims to capture some of the recent advances in the ?eld of CNN research and a few select areas of applications.
Download or read book Universality and Emergent Computation in Cellular Neural Networks written by Radu Dogaru and published by World Scientific. This book was released on 2003 with total page 262 pages. Available in PDF, EPUB and Kindle. Book excerpt: Cellular computing is a natural information processing paradigm, capable of modeling various biological, physical and social phenomena, as well as other kinds of complex adaptive systems. The programming of a cellular computer is in many respects similar to the genetic evolution in biology, the result being a proper cell design and a task-specific gene.How should one ?program? the cell of a cellular computer such that a dynamic behavior with computational relevance will emerge? What are the ?rules? for designing a computationally universal and efficient cell?The answers to those questions can be found in this book. It introduces the relatively new paradigm of the cellular neural network from an original perspective and provides the reader with the guidelines for understanding how such cellular computers can be ?programmed? and designed optimally. The book contains numerous practical examples and software simulators, allowing readers to experiment with the various phases of designing cellular computers by themselves.
Download or read book Cellular Neural Networks and Their Applications written by and published by World Scientific. This book was released on 2002 with total page 704 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume covers the fundamental theory of Cellular Neural Networks as well as their applications in various fields such as science and technology. It contains all 83 papers of the 7th International Workshop on Cellular Neural Networks and their Applications. The workshop follows a biennial series of six workshops consecutively hosted in Budapest (1990), Munich, Rome, Seville, London and Catania (2000).
Download or read book Towards the Visual Microprocessor written by Tamás Roska and published by John Wiley & Sons. This book was released on 2001-01-17 with total page 438 pages. Available in PDF, EPUB and Kindle. Book excerpt: Written by a group of leading researchers in the field, this is a pioneering work, providing a concise analysis of the topic by the inventors of the CNN universal machine and the supercomputer chip. Opening with a foreword by the respected academic, Professor Leon Chua, the book progresses to explore circuit design, prototyping and analogical algorithms. Subjects covered include the VLSI design and implementation of CNNs, the testing of CNN chips and a detailed analysis of the new system for prototyping and interfacing the CNN universal chips ? Includes applications in: Neurocomputing, Machine Vision, Image Processing and VLSI Signal Processing ? Provides simple algorithms to design and synthesise complex circuits ? Written and edited by world authorities in this field, including Leon Chua who invented CNNs in the late 1980s. This text follows on from Roska's previous success - Cellular Neural Networks and D3 - with this groundbreaking work about a rapidly developing and increasingly influential field of circuit theory. This text would be of great interest to a broad audience including postgraduate and advanced students, researchers and professionals in electrical and electronic engineering, computer science, mathematics and neurobiology.
Download or read book Recent Metaheuristic Computation Schemes in Engineering written by Erik Cuevas and published by Springer Nature. This book was released on 2021-02-04 with total page 282 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book includes two objectives. The first goal is to present advances and developments which have proved to be effective in their application to several complex problems. The second objective is to present the performance comparison of various metaheuristic techniques when they face complex optimization problems. The material has been compiled from a teaching perspective. Most of the problems in science, engineering, economics, and other areas can be translated as an optimization or a search problem. According to their characteristics, some problems can be simple that can be solved by traditional optimization methods based on mathematical analysis. However, most of the problems of practical importance in engineering represent complex scenarios so that they are very hard to be solved by using traditional approaches. Under such circumstances, metaheuristic has emerged as the best alternative to solve this kind of complex formulations. This book is primarily intended for undergraduate and postgraduate students. Engineers and application developers can also benefit from the book contents since it has been structured so that each chapter can be read independently from the others, and therefore, only potential interesting information can be quickly available for solving an industrial problem at hand.
Download or read book Cellular Neural Networks Multi scroll Chaos and Synchronization written by M?tak E. Yalin and published by World Scientific. This book was released on 2005 with total page 248 pages. Available in PDF, EPUB and Kindle. Book excerpt: For engineering applications that are based on nonlinear phenomena, novel information processing systems require new methodologies and design principles. This perspective is the basis of the three cornerstones of this book: cellular neural networks, chaos and synchronization. Cellular neural networks and their universal machine implementations offer a well-established platform for processing spatial-temporal patterns and wave computing. Multi-scroll circuits are generalizations to the original Chua's circuit, leading to chip implementable circuits with increasingly complex attractors. Several applications make use of synchronization techniques for nonlinear systems. A systematic overview is given for Lur'e representable systems with global synchronization criteria for master-slave and mutual synchronization, robust synchronization, HV synchronization, time-delayed systems and impulsive synchronization.
Download or read book Cellular Neural Networks written by Angela Slavova and published by Nova Publishers. This book was released on 2004 with total page 218 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book deals with new theoretical results for studyingCellular Neural Networks (CNNs) concerning its dynamical behavior. Newaspects of CNNs' applications are developed for modelling of somefamous nonlinear partial differential equations arising in biology, genetics, neurophysiology, physics, ecology, etc. The analysis ofCNNs' models is based on the harmonic balance method well known incontrol theory and in the study of electronic oscillators. Suchphenomena as hysteresis, bifurcation and chaos are studied for CNNs.The topics investigated in the book involve several scientificdisciplines, such as dynamical systems, applied mathematics, mathematical modelling, information processing, biology andneurophysiology. The reader will find comprehensive discussion on thesubject as well as rigorous mathematical analyses of networks ofneurons from the view point of dynamical systems. The text is writtenas a textbook for senior undergraduate and graduate students inapplied mathematics. Providing a summary of recent results on dynamicsand modelling of CNNs, the book will also be of interest to allresearchers in the area.
Download or read book Cellular Neural Networks written by Tamás Roska and published by Wiley. This book was released on 1994-01-25 with total page 236 pages. Available in PDF, EPUB and Kindle. Book excerpt: Cellular Neural Networks Edited by T. Roska, Computer & Automation Institute, Hungarian Academy of Sciences J. Vandewalle, Katholieke Universiteit Leuven, Belgium Written by a team of well-known researchers, this unique book and software package covers all the recent developments in, and applications of, cellular neural networks. The text is divided into four sections, detailing the theory, VLSI realization, design tools and applications of CNNs. Features include: The design of high-speed, high-density CNNs in CMOS technology. Testability in analogue cellular neural networks. The practical applications of CNNs including the detection of moving and stationary objects, and the use of cellular neural networks for solving specific image-processing problems. A versatile CNN software simulator accompanies the book. Designed for standard PCs under MS DOS, this user-friendly program allows users to visualize and test their own ideas. The 3.5" disk and user’s manual form an essential part of this package. The wide-ranging applications of cellular neural networks and the ease of VLSI implementation have ensured that CNNs are now a major new research area. This comprehensive package will provide valuable guidance for advanced students and researchers in electrical and electronic engineering and computer science. Neurobilogists and mathematicians will also find the package appealing.
Download or read book Cellular Neural Networks Dynamics and Modelling written by A. Slavova and published by Springer Science & Business Media. This book was released on 2013-06-29 with total page 230 pages. Available in PDF, EPUB and Kindle. Book excerpt: Conventional digital computation methods have run into a se rious speed bottleneck due to their serial nature. To overcome this problem, a new computation model, called Neural Networks, has been proposed, which is based on some aspects of neurobiology and adapted to integrated circuits. The increased availability of com puting power has not only made many new applications possible but has also created the desire to perform cognitive tasks which are easily carried out by the human brain. It become obvious that new types of algorithms and/or circuits were necessary to cope with such tasks. Inspiration has been sought from the functioning of the hu man brain, which led to the artificial neural network approach. One way of looking at neural networks is to consider them to be arrays of nonlinear dynamical systems that interact with each other. This book deals with one class of locally coupled neural net works, called Cellular Neural Networks (CNNs). CNNs were intro duced in 1988 by L. O. Chua and L. Yang [27,28] as a novel class of information processing systems, which posseses some of the key fea tures of neural networks (NNs) and which has important potential applications in such areas as image processing and pattern reco gnition. Unfortunately, the highly interdisciplinary nature of the research in CNNs makes it very difficult for a newcomer to enter this important and fasciriating area of modern science.
Download or read book A Guide to Convolutional Neural Networks for Computer Vision written by Salman Khan and published by Morgan & Claypool Publishers. This book was released on 2018-02-13 with total page 303 pages. Available in PDF, EPUB and Kindle. Book excerpt: Computer vision has become increasingly important and effective in recent years due to its wide-ranging applications in areas as diverse as smart surveillance and monitoring, health and medicine, sports and recreation, robotics, drones, and self-driving cars. Visual recognition tasks, such as image classification, localization, and detection, are the core building blocks of many of these applications, and recent developments in Convolutional Neural Networks (CNNs) have led to outstanding performance in these state-of-the-art visual recognition tasks and systems. As a result, CNNs now form the crux of deep learning algorithms in computer vision. This self-contained guide will benefit those who seek to both understand the theory behind CNNs and to gain hands-on experience on the application of CNNs in computer vision. It provides a comprehensive introduction to CNNs starting with the essential concepts behind neural networks: training, regularization, and optimization of CNNs. The book also discusses a wide range of loss functions, network layers, and popular CNN architectures, reviews the different techniques for the evaluation of CNNs, and presents some popular CNN tools and libraries that are commonly used in computer vision. Further, this text describes and discusses case studies that are related to the application of CNN in computer vision, including image classification, object detection, semantic segmentation, scene understanding, and image generation. This book is ideal for undergraduate and graduate students, as no prior background knowledge in the field is required to follow the material, as well as new researchers, developers, engineers, and practitioners who are interested in gaining a quick understanding of CNN models.
Download or read book Systematic Design for Emergence in Cellular Nonlinear Networks written by Radu Dogaru and published by Springer Science & Business Media. This book was released on 2008-02-01 with total page 174 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this insightful work, Dogaru proposes a systematic framework for measuring emergence and a systematic design method to locate computationally meaningful genes in a reasonable computing time. Programs and application examples are provided so that the reader may easily understand the new concepts and develop her own specific experiments. The book’s approachability recommends it to a large audience including specialists from various interdisciplinary fields.
Download or read book Artificial Intelligence and Quantum Computing for Advanced Wireless Networks written by Savo G. Glisic and published by John Wiley & Sons. This book was released on 2022-04-11 with total page 884 pages. Available in PDF, EPUB and Kindle. Book excerpt: ARTIFICIAL INTELLIGENCE AND QUANTUM COMPUTING FOR ADVANCED WIRELESS NETWORKS A comprehensive presentation of the implementation of artificial intelligence and quantum computing technology in large-scale communication networks Increasingly dense and flexible wireless networks require the use of artificial intelligence (AI) for planning network deployment, optimization, and dynamic control. Machine learning algorithms are now often used to predict traffic and network state in order to reserve resources for smooth communication with high reliability and low latency. In Artificial Intelligence and Quantum Computing for Advanced Wireless Networks, the authors deliver a practical and timely review of AI-based learning algorithms, with several case studies in both Python and R. The book discusses the game-theory-based learning algorithms used in decision making, along with various specific applications in wireless networks, like channel, network state, and traffic prediction. Additional chapters include Fundamentals of ML, Artificial Neural Networks (NN), Explainable and Graph NN, Learning Equilibria and Games, AI Algorithms in Networks, Fundamentals of Quantum Communications, Quantum Channel, Information Theory and Error Correction, Quantum Optimization Theory, and Quantum Internet, to name a few. The authors offer readers an intuitive and accessible path from basic topics on machine learning through advanced concepts and techniques in quantum networks. Readers will benefit from: A thorough introduction to the fundamentals of machine learning algorithms, including linear and logistic regression, decision trees, random forests, bagging, boosting, and support vector machines An exploration of artificial neural networks, including multilayer neural networks, training and backpropagation, FIR architecture spatial-temporal representations, quantum ML, quantum information theory, fundamentals of quantum internet, and more Discussions of explainable neural networks and XAI Examinations of graph neural networks, including learning algorithms and linear and nonlinear GNNs in both classical and quantum computing technology Perfect for network engineers, researchers, and graduate and masters students in computer science and electrical engineering, Artificial Intelligence and Quantum Computing for Advanced Wireless Networks is also an indispensable resource for IT support staff, along with policymakers and regulators who work in technology.
