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Convergence Analysis Of Recurrent Neural Networks

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Convergence Analysis Of Recurrent Neural Networks

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Author : Zhang Yi
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-11-11

Convergence Analysis Of Recurrent Neural Networks written by Zhang Yi and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-11-11 with Computers categories.

Since the outstanding and pioneering research work of Hopfield on recurrent neural networks (RNNs) in the early 80s of the last century, neural networks have rekindled strong interests in scientists and researchers. Recent years have recorded a remarkable advance in research and development work on RNNs, both in theoretical research as weIl as actual applications. The field of RNNs is now transforming into a complete and independent subject. From theory to application, from software to hardware, new and exciting results are emerging day after day, reflecting the keen interest RNNs have instilled in everyone, from researchers to practitioners. RNNs contain feedback connections among the neurons, a phenomenon which has led rather naturally to RNNs being regarded as dynamical systems. RNNs can be described by continuous time differential systems, discrete time systems, or functional differential systems, and more generally, in terms of non linear systems. Thus, RNNs have to their disposal, a huge set of mathematical tools relating to dynamical system theory which has tumed out to be very useful in enabling a rigorous analysis of RNNs.

Neural Networks Computational Models And Applications

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Author : Huajin Tang
language : en
Publisher: Springer Science & Business Media
Release Date : 2007-03-12

Neural Networks Computational Models And Applications written by Huajin Tang and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007-03-12 with Computers categories.

Neural Networks: Computational Models and Applications presents important theoretical and practical issues in neural networks, including the learning algorithms of feed-forward neural networks, various dynamical properties of recurrent neural networks, winner-take-all networks and their applications in broad manifolds of computational intelligence: pattern recognition, uniform approximation, constrained optimization, NP-hard problems, and image segmentation. The book offers a compact, insightful understanding of the broad and rapidly growing neural networks domain.

Complex Valued Neural Networks

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Author : Akira Hirose
language : en
Publisher: World Scientific
Release Date : 2003

Complex Valued Neural Networks written by Akira Hirose and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2003 with Computers categories.

In recent years, complex-valued neural networks have widened the scope of application in optoelectronics, imaging, remote sensing, quantum neural devices and systems, spatiotemporal analysis of physiological neural systems, and artificial neural information processing. In this first-ever book on complex-valued neural networks, the most active scientists at the forefront of the field describe theories and applications from various points of view to provide academic and industrial researchers with a comprehensive understanding of the fundamentals, features and prospects of the powerful complex-valued networks.

Advances In Neural Networks Isnn 2006

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Author :
language : en
Publisher: Springer Science & Business Media
Release Date : 2006

Advances In Neural Networks Isnn 2006 written by and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006 with Artificial intelligence categories.

Computational Intelligence And Intelligent Systems

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Author : Kangshun Li
language : en
Publisher: Springer
Release Date : 2018-07-20

Computational Intelligence And Intelligent Systems written by Kangshun Li and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-07-20 with Computers categories.

This two-volume set (CCIS 873 and CCIS 874) constitutes the thoroughly refereed proceedings of the 9th International Symposium, ISICA 2017, held in Guangzhou, China, in November 2017.The 101 full papers presented in both volumes were carefully reviewed and selected from 181 submissions. This first volume is organized in topical sections on neural networks and statistical learning: neural architecture search, transfer of knowledge; evolutionary multi-objective and dynamic optimization: optimal control and design, hybrid methods; data mining: association rule learning, data management platforms; Cloud computing and multiagent systems: service models, Cloud engineering; everywhere connectivity: IoT solutions, wireless sensor networks.

Issues In Artificial Intelligence Robotics And Machine Learning 2011 Edition

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Author :
language : en
Publisher: ScholarlyEditions
Release Date : 2012-01-09

Issues In Artificial Intelligence Robotics And Machine Learning 2011 Edition written by and has been published by ScholarlyEditions this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-01-09 with Computers categories.

Issues in Artificial Intelligence, Robotics and Machine Learning: 2011 Edition is a ScholarlyEditions™ eBook that delivers timely, authoritative, and comprehensive information about Artificial Intelligence, Robotics and Machine Learning. The editors have built Issues in Artificial Intelligence, Robotics and Machine Learning: 2011 Edition on the vast information databases of ScholarlyNews.™ You can expect the information about Artificial Intelligence, Robotics and Machine Learning in this eBook to be deeper than what you can access anywhere else, as well as consistently reliable, authoritative, informed, and relevant. The content of Issues in Artificial Intelligence, Robotics and Machine Learning: 2011 Edition has been produced by the world’s leading scientists, engineers, analysts, research institutions, and companies. All of the content is from peer-reviewed sources, and all of it is written, assembled, and edited by the editors at ScholarlyEditions™ and available exclusively from us. You now have a source you can cite with authority, confidence, and credibility. More information is available at http://www.ScholarlyEditions.com/.

Advances In Neural Networks Isnn 2010

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Author : James Kwok
language : en
Publisher: Springer
Release Date : 2010-05-30

Advances In Neural Networks Isnn 2010 written by James Kwok and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-05-30 with Computers categories.

This book and its sister volume collect refereed papers presented at the 7th Inter- tional Symposium on Neural Networks (ISNN 2010), held in Shanghai, China, June 6-9, 2010. Building on the success of the previous six successive ISNN symposiums, ISNN has become a well-established series of popular and high-quality conferences on neural computation and its applications. ISNN aims at providing a platform for scientists, researchers, engineers, as well as students to gather together to present and discuss the latest progresses in neural networks, and applications in diverse areas. Nowadays, the field of neural networks has been fostered far beyond the traditional artificial neural networks. This year, ISNN 2010 received 591 submissions from more than 40 countries and regions. Based on rigorous reviews, 170 papers were selected for publication in the proceedings. The papers collected in the proceedings cover a broad spectrum of fields, ranging from neurophysiological experiments, neural modeling to extensions and applications of neural networks. We have organized the papers into two volumes based on their topics. The first volume, entitled “Advances in Neural Networks- ISNN 2010, Part 1,” covers the following topics: neurophysiological foundation, theory and models, learning and inference, neurodynamics. The second volume en- tled “Advance in Neural Networks ISNN 2010, Part 2” covers the following five topics: SVM and kernel methods, vision and image, data mining and text analysis, BCI and brain imaging, and applications.

Complex Valued Neural Networks Theories And Applications

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Author : Akira Hirose
language : en
Publisher: World Scientific
Release Date : 2003-11-18

Complex Valued Neural Networks Theories And Applications written by Akira Hirose and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2003-11-18 with Computers categories.

Eighth International Work Conference On Artificial And Natural Neural Networks

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Author : Joan Cabestany
language : en
Publisher: Springer Science & Business Media
Release Date : 2005-05-30

Eighth International Work Conference On Artificial And Natural Neural Networks written by Joan Cabestany and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2005-05-30 with Computers categories.

We present in this volume the collection of finally accepted papers of the eighth edition of the “IWANN” conference (“International Work-Conference on Artificial Neural Networks”). This biennial meeting focuses on the foundations, theory, models and applications of systems inspired by nature (neural networks, fuzzy logic and evolutionary systems). Since the first edition of IWANN in Granada (LNCS 540, 1991), the Artificial Neural Network (ANN) community, and the domain itself, have matured and evolved. Under the ANN banner we find a very heterogeneous scenario with a main interest and objective: to better understand nature and beings for the correct elaboration of theories, models and new algorithms. For scientists, engineers and professionals working in the area, this is a very good way to get solid and competitive applications. We are facing a real revolution with the emergence of embedded intelligence in many artificial systems (systems covering diverse fields: industry, domotics, leisure, healthcare, ... ). So we are convinced that an enormous amount of work must be, and should be, still done. Many pieces of the puzzle must be built and placed into their proper positions, offering us new and solid theories and models (necessary tools) for the application and praxis of these current paradigms. The above-mentioned concepts were the main reason for the subtitle of the IWANN 2005 edition: “Computational Intelligence and Bioinspired Systems.” The call for papers was launched several months ago, addressing the following topics: 1. Mathematical and theoretical methods in computational intelligence.

High Dimensional Optimization And Probability

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Author : Ashkan Nikeghbali
language : en
Publisher: Springer Nature
Release Date : 2022-08-04

High Dimensional Optimization And Probability written by Ashkan Nikeghbali and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-08-04 with Mathematics categories.

This volume presents extensive research devoted to a broad spectrum of mathematics with emphasis on interdisciplinary aspects of Optimization and Probability. Chapters also emphasize applications to Data Science, a timely field with a high impact in our modern society. The discussion presents modern, state-of-the-art, research results and advances in areas including non-convex optimization, decentralized distributed convex optimization, topics on surrogate-based reduced dimension global optimization in process systems engineering, the projection of a point onto a convex set, optimal sampling for learning sparse approximations in high dimensions, the split feasibility problem, higher order embeddings, codifferentials and quasidifferentials of the expectation of nonsmooth random integrands, adjoint circuit chains associated with a random walk, analysis of the trade-off between sample size and precision in truncated ordinary least squares, spatial deep learning, efficient location-based tracking for IoT devices using compressive sensing and machine learning techniques, and nonsmooth mathematical programs with vanishing constraints in Banach spaces. The book is a valuable source for graduate students as well as researchers working on Optimization, Probability and their various interconnections with a variety of other areas. Chapter 12 is available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.

Convergence Analysis Of Recurrent Neural Networks

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