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EBookClubs

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Book Progress in Neural Networks

Download or read book Progress in Neural Networks written by and published by . This book was released on 1997 with total page 342 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book Artificial Intelligence in the Age of Neural Networks and Brain Computing

Download or read book Artificial Intelligence in the Age of Neural Networks and Brain Computing written by Robert Kozma and published by Academic Press. This book was released on 2023-10-27 with total page 398 pages. Available in PDF, EPUB and Kindle. Book excerpt: Artificial Intelligence in the Age of Neural Networks and Brain Computing, Second Edition demonstrates that present disruptive implications and applications of AI is a development of the unique attributes of neural networks, mainly machine learning, distributed architectures, massive parallel processing, black-box inference, intrinsic nonlinearity, and smart autonomous search engines. The book covers the major basic ideas of "brain-like computing" behind AI, provides a framework to deep learning, and launches novel and intriguing paradigms as possible future alternatives. The present success of AI-based commercial products proposed by top industry leaders, such as Google, IBM, Microsoft, Intel, and Amazon, can be interpreted using the perspective presented in this book by viewing the co-existence of a successful synergism among what is referred to as computational intelligence, natural intelligence, brain computing, and neural engineering. The new edition has been updated to include major new advances in the field, including many new chapters. Developed from the 30th anniversary of the International Neural Network Society (INNS) and the 2017 International Joint Conference on Neural Networks (IJCNN Authored by top experts, global field pioneers, and researchers working on cutting-edge applications in signal processing, speech recognition, games, adaptive control and decision-making Edited by high-level academics and researchers in intelligent systems and neural networks Includes all new chapters, including topics such as Frontiers in Recurrent Neural Network Research; Big Science, Team Science, Open Science for Neuroscience; A Model-Based Approach for Bridging Scales of Cortical Activity; A Cognitive Architecture for Object Recognition in Video; How Brain Architecture Leads to Abstract Thought; Deep Learning-Based Speech Separation and Advances in AI, Neural Networks

Book Progress in Neural Networks  Volume Five

Download or read book Progress in Neural Networks Volume Five written by Charles L. Wilson and published by Intellect Books. This book was released on 1997 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume has a special thematic focus on the architecture of neural networks. It is part of a series that reviews research in natural and synthetic neural networks, as well as research in modelling, analysis, design, and development of neural networks in software and hardware areas. Contributions from researchers and practitioners serve as a platform for discussion of topics of interest to the neural network and cognitive information processing communities.

Book Advances in Neural Networks  Computational and Theoretical Issues

Download or read book Advances in Neural Networks Computational and Theoretical Issues written by Simone Bassis and published by Springer. This book was released on 2015-06-05 with total page 392 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book collects research works that exploit neural networks and machine learning techniques from a multidisciplinary perspective. Subjects covered include theoretical, methodological and computational topics which are grouped together into chapters devoted to the discussion of novelties and innovations related to the field of Artificial Neural Networks as well as the use of neural networks for applications, pattern recognition, signal processing, and special topics such as the detection and recognition of multimodal emotional expressions and daily cognitive functions, and bio-inspired memristor-based networks. Providing insights into the latest research interest from a pool of international experts coming from different research fields, the volume becomes valuable to all those with any interest in a holistic approach to implement believable, autonomous, adaptive and context-aware Information Communication Technologies.

Book Neural Networks and Analog Computation

Download or read book Neural Networks and Analog Computation written by Hava T. Siegelmann and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 193 pages. Available in PDF, EPUB and Kindle. Book excerpt: The theoretical foundations of Neural Networks and Analog Computation conceptualize neural networks as a particular type of computer consisting of multiple assemblies of basic processors interconnected in an intricate structure. Examining these networks under various resource constraints reveals a continuum of computational devices, several of which coincide with well-known classical models. On a mathematical level, the treatment of neural computations enriches the theory of computation but also explicated the computational complexity associated with biological networks, adaptive engineering tools, and related models from the fields of control theory and nonlinear dynamics. The material in this book will be of interest to researchers in a variety of engineering and applied sciences disciplines. In addition, the work may provide the base of a graduate-level seminar in neural networks for computer science students.

Book Radial Basis Function Neural Networks with Sequential Learning

Download or read book Radial Basis Function Neural Networks with Sequential Learning written by N. Sundararajan and published by World Scientific. This book was released on 1999 with total page 236 pages. Available in PDF, EPUB and Kindle. Book excerpt: A review of radial basis founction (RBF) neural networks. A novel sequential learning algorithm for minimal resource allocation neural networks (MRAN). MRAN for function approximation & pattern classification problems; MRAN for nonlinear dynamic systems; MRAN for communication channel equalization; Concluding remarks; A outline source code for MRAN in MATLAB; Bibliography; Index.

Book Advances in Deep Learning

Download or read book Advances in Deep Learning written by M. Arif Wani and published by Springer. This book was released on 2019-03-14 with total page 149 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book introduces readers to both basic and advanced concepts in deep network models. It covers state-of-the-art deep architectures that many researchers are currently using to overcome the limitations of the traditional artificial neural networks. Various deep architecture models and their components are discussed in detail, and subsequently illustrated by algorithms and selected applications. In addition, the book explains in detail the transfer learning approach for faster training of deep models; the approach is also demonstrated on large volumes of fingerprint and face image datasets. In closing, it discusses the unique set of problems and challenges associated with these models.

Book Progress in Neural Networks

Download or read book Progress in Neural Networks written by Omid Omidvar and published by Intellect Books. This book was released on 1994 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This series reviews research in natural and synthetic neural networks, as well as reviews research in modelling, analysis, design and development of neural networks in software and hardware areas. Contributions from researchers and practitioners aim to shape academic and professional programs in this area, and serve as a platform for detailed and expanded discussion of topics of interest to the neural network and cognitive information processing communities. This series should be of interest to those professionally involved in neural networks research, such as lecturers and primary investigators in neural computing, modelling, learning, memory and neurocomputers.

Book Advances in Neural Networks

Download or read book Advances in Neural Networks written by Fuchun Sun and published by Springer Science & Business Media. This book was released on 2008-09-08 with total page 939 pages. Available in PDF, EPUB and Kindle. Book excerpt: (Bayreuth University, Germany), Jennie Si (Arizona State University, USA), and Hang Li (MicrosoftResearchAsia, China). Besides the regularsessions andpanels, ISNN 2008 also featured four special sessions focusing on some emerging topics.

Book Recent Advances in Artificial Neural Networks

Download or read book Recent Advances in Artificial Neural Networks written by L. C. Jain and published by CRC Press. This book was released on 2018-05-04 with total page 372 pages. Available in PDF, EPUB and Kindle. Book excerpt: Neural networks represent a new generation of information processing paradigms designed to mimic-in a very limited sense-the human brain. They can learn, recall, and generalize from training data, and with their potential applications limited only by the imaginations of scientists and engineers, they are commanding tremendous popularity and research interest. Over the last four decades, researchers have reported a number of neural network paradigms, however, the newest of these have not appeared in book form-until now. Recent Advances in Artificial Neural Networks collects the latest neural network paradigms and reports on their promising new applications. World-renowned experts discuss the use of neural networks in pattern recognition, color induction, classification, cluster detection, and more. Application engineers, scientists, and research students from all disciplines with an interest in considering neural networks for solving real-world problems will find this collection useful.

Book Radial Basis Function Neural Networks With Sequential Learning  Progress In Neural Processing

Download or read book Radial Basis Function Neural Networks With Sequential Learning Progress In Neural Processing written by Ying Wei Lu and published by World Scientific. This book was released on 1999-10-04 with total page 231 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents in detail the newly developed sequential learning algorithm for radial basis function neural networks, which realizes a minimal network. This algorithm, created by the authors, is referred to as Minimal Resource Allocation Networks (MRAN). The book describes the application of MRAN in different areas, including pattern recognition, time series prediction, system identification, control, communication and signal processing. Benchmark problems from these areas have been studied, and MRAN is compared with other algorithms. In order to make the book self-contained, a review of the existing theory of RBF networks and applications is given at the beginning.

Book Progress in Neural Networks  Volume Four

Download or read book Progress in Neural Networks Volume Four written by Omid M. Omidvar and published by Intellect (UK). This book was released on 1997 with total page 328 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is a study of the use of neural networks for machine vision. It is part of a series which reviews research in natural and synthetic neural networks, as well as in modelling, analysis, design, and development of neural networks in software and hardware areas. Contributions from researchers and practitioners serve as a platform for discussion of topics of interest to the neural network and cognitive information processing communities.

Book Progress in neural networks

Download or read book Progress in neural networks written by Omid Omidvar and published by . This book was released on 1991 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book Advances in Neural Networks     ISNN 2020

Download or read book Advances in Neural Networks ISNN 2020 written by Min Han and published by Springer Nature. This book was released on 2020-11-28 with total page 284 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume LNCS 12557 constitutes the refereed proceedings of the 17th International Symposium on Neural Networks, ISNN 2020, held in Cairo, Egypt, in December 2020. The 24 papers presented in the two volumes were carefully reviewed and selected from 39 submissions. The papers were organized in topical sections named: optimization algorithms; neurodynamics, complex systems, and chaos; supervised/unsupervised/reinforcement learning/deep learning; models, methods and algorithms; and signal, image and video processing.

Book Advances in Neural Networks     ISNN 2024

Download or read book Advances in Neural Networks ISNN 2024 written by Xinyi Le and published by Springer Nature. This book was released on with total page 635 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book Advances in Neural Networks     ISNN 2018

Download or read book Advances in Neural Networks ISNN 2018 written by Tingwen Huang and published by Springer. This book was released on 2018-05-25 with total page 872 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 15th International Symposium on Neural Networks, ISNN 2018, held in Minsk, Belarus in June 2018.The 98 revised regular papers presented in this volume were carefully reviewed and selected from 214 submissions. The papers cover many topics of neural network-related research including intelligent control, neurodynamic analysis, bio-signal, bioinformatics and biomedical engineering, clustering, classification, forecasting, models, algorithms, cognitive computation, machine learning, and optimization.​

Book Machine Learning for Societal Improvement  Modernization  and Progress

Download or read book Machine Learning for Societal Improvement Modernization and Progress written by Pendyala, Vishnu S. and published by IGI Global. This book was released on 2022-06-24 with total page 307 pages. Available in PDF, EPUB and Kindle. Book excerpt: Learning has been fundamental to the growth and evolution of humanity and civilization. The same concepts of learning, applied to the tasks that machines can perform, are having a similar effect now. Machine learning is evolving computation and its applications like never before. It is now widely recognized that machine learning is playing a similar role to electricity in the late 19th and early 20th centuries in modernizing the world. From simple high school science projects to large-scale radio astronomy, machine learning has revolutionized it all—however, a few of the applications clearly stand out as transforming the world and opening up a new era. Machine Learning for Societal Improvement, Modernization, and Progress showcases the path-breaking applications of machine learning that are leading to the next generation of computing and living standards. The focus of the book is machine learning and its application to specific domains, which is resulting in substantial civilizational progress. Covering topics such as lifespan prediction, smart transportation networks, and socio-economic data, this premier reference source is a dynamic resource for data scientists, industry leaders, practitioners, students and faculty of higher education, sociologists, researchers, and academicians.