Nonlinear Optimization Approaches For Training Neural Networks
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Nonlinear Optimization Approaches For Training Neural Networks
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Author : George Magoulas
language : en
Publisher: Springer
Release Date : 2015-12-24
Nonlinear Optimization Approaches For Training Neural Networks written by George Magoulas and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-12-24 with Mathematics categories.
This book examines how nonlinear optimization techniques can be applied to training and testing neural networks. It includes both well-known and recently-developed network training methods including deterministic nonlinear optimization methods, stochastic nonlinear optimization methods, and advanced training schemes which combine both deterministic and stochastic components. The convergence analysis and convergence proofs of these techniques are presented as well as real applications of neural networks in areas such as pattern classification, bioinformatics, biomedicine, and finance. Nonlinear optimization methods are applied extensively in the design of training protocols for artificial neural networks used in industry and academia. Such techniques allow for the implementation of dynamic unsupervised neural network training without requiring the fine tuning of several heuristic parameters. "Nonlinear Optimization Approaches for Training Neural Networks" is a response to the growing demand for innovations in this area of research. This monograph presents a wide range of approaches to neural networks training providing theoretical justification for network behavior based on the theory of nonlinear optimization. It presents training algorithms, and theoretical results on their convergence and implementations through pseudocode. This approach offers the reader an explanation of the performance of the various methods, and a better understanding of the individual characteristics of the various methods, their differences/advantages and interrelationships. This improved perspective allows the reader to choose the best network training method without spending too much effort configuring highly sensitive heuristic parameters. This book can serve as an excellent guide for researchers, graduate students, and lecturers interested in the development of neural networks and their training.
Nonlinear System Identification
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Author : Oliver Nelles
language : en
Publisher: Springer Nature
Release Date : 2020-09-09
Nonlinear System Identification written by Oliver Nelles and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-09-09 with Science categories.
This book provides engineers and scientists in academia and industry with a thorough understanding of the underlying principles of nonlinear system identification. It equips them to apply the models and methods discussed to real problems with confidence, while also making them aware of potential difficulties that may arise in practice. Moreover, the book is self-contained, requiring only a basic grasp of matrix algebra, signals and systems, and statistics. Accordingly, it can also serve as an introduction to linear system identification, and provides a practical overview of the major optimization methods used in engineering. The focus is on gaining an intuitive understanding of the subject and the practical application of the techniques discussed. The book is not written in a theorem/proof style; instead, the mathematics is kept to a minimum, and the ideas covered are illustrated with numerous figures, examples, and real-world applications. In the past, nonlinear system identification was a field characterized by a variety of ad-hoc approaches, each applicable only to a very limited class of systems. With the advent of neural networks, fuzzy models, Gaussian process models, and modern structure optimization techniques, a much broader class of systems can now be handled. Although one major aspect of nonlinear systems is that virtually every one is unique, tools have since been developed that allow each approach to be applied to a wide variety of systems.
Nonlinear System Identification
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Author : Oliver Nelles
language : en
Publisher: Springer Science & Business Media
Release Date : 2001
Nonlinear System Identification written by Oliver Nelles 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 2001 with Computers categories.
Written from an engineering point of view, this book covers the most common and important approaches for the identification of nonlinear static and dynamic systems. The book also provides the reader with the necessary background on optimization techniques, making it fully self-contained. The new edition includes exercises.
Advances In Neural Networks Research
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Author : D.C. Wunsch II
language : en
Publisher: Elsevier
Release Date : 2003-08-22
Advances In Neural Networks Research written by D.C. Wunsch II and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2003-08-22 with Computers categories.
IJCNN is the flagship conference of the INNS, as well as the IEEE Neural Networks Society. It has arguably been the preeminent conference in the field, even as neural network conferences have proliferated and specialized. As the number of conferences has grown, its strongest competition has migrated away from an emphasis on neural networks. IJCNN has embraced the proliferation of spin-off and related fields (see the topic list, below), while maintaining a core emphasis befitting its name. It has also succeeded in enforcing an emphasis on quality.
Advances In Evolutionary And Deterministic Methods For Design Optimization And Control In Engineering And Sciences
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Author : David Greiner
language : en
Publisher: Springer
Release Date : 2014-11-14
Advances In Evolutionary And Deterministic Methods For Design Optimization And Control In Engineering And Sciences written by David Greiner and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-11-14 with Technology & Engineering categories.
This book contains state-of-the-art contributions in the field of evolutionary and deterministic methods for design, optimization and control in engineering and sciences. Specialists have written each of the 34 chapters as extended versions of selected papers presented at the International Conference on Evolutionary and Deterministic Methods for Design, Optimization and Control with Applications to Industrial and Societal Problems (EUROGEN 2013). The conference was one of the Thematic Conferences of the European Community on Computational Methods in Applied Sciences (ECCOMAS). Topics treated in the various chapters are classified in the following sections: theoretical and numerical methods and tools for optimization (theoretical methods and tools; numerical methods and tools) and engineering design and societal applications (turbo machinery; structures, materials and civil engineering; aeronautics and astronautics; societal applications; electrical and electronics applications), focused particularly on intelligent systems for multidisciplinary design optimization (mdo) problems based on multi-hybridized software, adjoint-based and one-shot methods, uncertainty quantification and optimization, multidisciplinary design optimization, applications of game theory to industrial optimization problems, applications in structural and civil engineering optimum design and surrogate models based optimization methods in aerodynamic design.
Encyclopedia Of Optimization
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Author : Christodoulos A. Floudas
language : en
Publisher: Springer Science & Business Media
Release Date : 2008-09-04
Encyclopedia Of Optimization written by Christodoulos A. Floudas 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 2008-09-04 with Mathematics categories.
The goal of the Encyclopedia of Optimization is to introduce the reader to a complete set of topics that show the spectrum of research, the richness of ideas, and the breadth of applications that has come from this field. The second edition builds on the success of the former edition with more than 150 completely new entries, designed to ensure that the reference addresses recent areas where optimization theories and techniques have advanced. Particularly heavy attention resulted in health science and transportation, with entries such as "Algorithms for Genomics", "Optimization and Radiotherapy Treatment Design", and "Crew Scheduling".
Neural Nets Wirn Vietri 95 Proceedings Of The Vii Italian Workshop
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Author : Maria Marinaro
language : en
Publisher: World Scientific
Release Date : 1996-01-29
Neural Nets Wirn Vietri 95 Proceedings Of The Vii Italian Workshop written by Maria Marinaro and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 1996-01-29 with categories.
This volume contains the proceedings of the seventh Italian Workshop on Neural Nets WIRN VIETRI '95, organized by the International Institute for Advanced Scientific Studies 'E R Caianiello' (IIASS) and Società Italiana Reti Neuroniche (SIREN).The spectrum of contributors and participants covers the activity of Italian research in the field. The papers of the two invited speakers, M J Jordan ('Sigmoid Belief Networks') and E Oja ('Principal and Independent Component Analysis'), and the two reviews ('Fast Learning Algorithms for Feedforward NN' and 'ANN Ensembles: a Bayesian Standpoint') complete the highly qualified contents of the volume.
Nonlinear System Identification
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Author : Oliver Nelles
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-03-09
Nonlinear System Identification written by Oliver Nelles 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 2013-03-09 with Technology & Engineering categories.
Written from an engineering point of view, this book covers the most common and important approaches for the identification of nonlinear static and dynamic systems. The book also provides the reader with the necessary background on optimization techniques, making it fully self-contained. The new edition includes exercises.
Learning From Data
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Author : Vladimir Cherkassky
language : en
Publisher: John Wiley & Sons
Release Date : 2007-09-10
Learning From Data written by Vladimir Cherkassky and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007-09-10 with Computers categories.
An interdisciplinary framework for learning methodologies—covering statistics, neural networks, and fuzzy logic, this book provides a unified treatment of the principles and methods for learning dependencies from data. It establishes a general conceptual framework in which various learning methods from statistics, neural networks, and fuzzy logic can be applied—showing that a few fundamental principles underlie most new methods being proposed today in statistics, engineering, and computer science. Complete with over one hundred illustrations, case studies, and examples making this an invaluable text.
Reinforcement Learning And Approximate Dynamic Programming For Feedback Control
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Author : Frank L. Lewis
language : en
Publisher: John Wiley & Sons
Release Date : 2013-01-28
Reinforcement Learning And Approximate Dynamic Programming For Feedback Control written by Frank L. Lewis and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-01-28 with Technology & Engineering categories.
Reinforcement learning (RL) and adaptive dynamic programming (ADP) has been one of the most critical research fields in science and engineering for modern complex systems. This book describes the latest RL and ADP techniques for decision and control in human engineered systems, covering both single player decision and control and multi-player games. Edited by the pioneers of RL and ADP research, the book brings together ideas and methods from many fields and provides an important and timely guidance on controlling a wide variety of systems, such as robots, industrial processes, and economic decision-making.