Multilayer Neural Networks
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Multilayer Neural Networks
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Author : Maciej Krawczak
language : en
Publisher: Springer
Release Date : 2013-04-17
Multilayer Neural Networks written by Maciej Krawczak and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-04-17 with Technology & Engineering categories.
The primary purpose of this book is to show that a multilayer neural network can be considered as a multistage system, and then that the learning of this class of neural networks can be treated as a special sort of the optimal control problem. In this way, the optimal control problem methodology, like dynamic programming, with modifications, can yield a new class of learning algorithms for multilayer neural networks. Another purpose of this book is to show that the generalized net theory can be successfully used as a new description of multilayer neural networks. Several generalized net descriptions of neural networks functioning processes are considered, namely: the simulation process of networks, a system of neural networks and the learning algorithms developed in this book. The generalized net approach to modelling of real systems may be used successfully for the description of a variety of technological and intellectual problems, it can be used not only for representing the parallel functioning of homogenous objects, but also for modelling non-homogenous systems, for example systems which consist of a different kind of subsystems. The use of the generalized nets methodology shows a new way to describe functioning of discrete dynamic systems.
Neural Networks Theory
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Author : Alexander I. Galushkin
language : en
Publisher: Springer Science & Business Media
Release Date : 2007-10-29
Neural Networks Theory written by Alexander I. Galushkin 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 2007-10-29 with Technology & Engineering categories.
This book, written by a leader in neural network theory in Russia, uses mathematical methods in combination with complexity theory, nonlinear dynamics and optimization. It details more than 40 years of Soviet and Russian neural network research and presents a systematized methodology of neural networks synthesis. The theory is expansive: covering not just traditional topics such as network architecture but also neural continua in function spaces as well.
Artificial Neural Networks Formal Models And Their Applications Icann 2005
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Author : Wlodzislaw Duch
language : en
Publisher: Springer
Release Date : 2005-08-25
Artificial Neural Networks Formal Models And Their Applications Icann 2005 written by Wlodzislaw Duch and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2005-08-25 with Computers categories.
This volume is the first part of the two-volume proceedings of the International C- ference on Artificial Neural Networks (ICANN 2005), held on September 11–15, 2005 in Warsaw, Poland, with several accompanying workshops held on September 15, 2005 at the Nicolaus Copernicus University, Toru , Poland. The ICANN conference is an annual meeting organized by the European Neural Network Society in cooperation with the International Neural Network Society, the Japanese Neural Network Society, and the IEEE Computational Intelligence Society. It is the premier European event covering all topics concerned with neural networks and related areas. The ICANN series of conferences was initiated in 1991 and soon became the major European gathering for experts in those fields. In 2005 the ICANN conference was organized by the Systems Research Institute, Polish Academy of Sciences, Warsaw, Poland, and the Nicolaus Copernicus Univ- sity, Toru , Poland. From over 600 papers submitted to the regular sessions and some 10 special c- ference sessions, the International Program Committee selected – after a thorough peer-review process – about 270 papers for publication. The large number of papers accepted is certainly a proof of the vitality and attractiveness of the field of artificial neural networks, but it also shows a strong interest in the ICANN conferences.
Complex Valued Neural Networks
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Author : Akira Hirose
language : en
Publisher: John Wiley & Sons
Release Date : 2013-05-08
Complex Valued Neural Networks written by Akira Hirose 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 2013-05-08 with Computers categories.
Presents the latest advances in complex-valued neural networks by demonstrating the theory in a wide range of applications Complex-valued neural networks is a rapidly developing neural network framework that utilizes complex arithmetic, exhibiting specific characteristics in its learning, self-organizing, and processing dynamics. They are highly suitable for processing complex amplitude, composed of amplitude and phase, which is one of the core concepts in physical systems to deal with electromagnetic, light, sonic/ultrasonic waves as well as quantum waves, namely, electron and superconducting waves. This fact is a critical advantage in practical applications in diverse fields of engineering, where signals are routinely analyzed and processed in time/space, frequency, and phase domains. Complex-Valued Neural Networks: Advances and Applications covers cutting-edge topics and applications surrounding this timely subject. Demonstrating advanced theories with a wide range of applications, including communication systems, image processing systems, and brain-computer interfaces, this text offers comprehensive coverage of: Conventional complex-valued neural networks Quaternionic neural networks Clifford-algebraic neural networks Presented by international experts in the field, Complex-Valued Neural Networks: Advances and Applications is ideal for advanced-level computational intelligence theorists, electromagnetic theorists, and mathematicians interested in computational intelligence, artificial intelligence, machine learning theories, and algorithms.
Complex Valued Neural Networks With Multi Valued Neurons
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Author : Igor Aizenberg
language : en
Publisher: Springer Science & Business Media
Release Date : 2011-06-24
Complex Valued Neural Networks With Multi Valued Neurons written by Igor Aizenberg 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 2011-06-24 with Computers categories.
Complex-Valued Neural Networks have higher functionality, learn faster and generalize better than their real-valued counterparts. This book is devoted to the Multi-Valued Neuron (MVN) and MVN-based neural networks. It contains a comprehensive observation of MVN theory, its learning, and applications. MVN is a complex-valued neuron whose inputs and output are located on the unit circle. Its activation function is a function only of argument (phase) of the weighted sum. MVN derivative-free learning is based on the error-correction rule. A single MVN can learn those input/output mappings that are non-linearly separable in the real domain. Such classical non-linearly separable problems as XOR and Parity n are the simplest that can be learned by a single MVN. Another important advantage of MVN is a proper treatment of the phase information. These properties of MVN become even more remarkable when this neuron is used as a basic one in neural networks. The Multilayer Neural Network based on Multi-Valued Neurons (MLMVN) is an MVN-based feedforward neural network. Its backpropagation learning algorithm is derivative-free and based on the error-correction rule. It does not suffer from the local minima phenomenon. MLMVN outperforms many other machine learning techniques in terms of learning speed, network complexity and generalization capability when solving both benchmark and real-world classification and prediction problems. Another interesting application of MVN is its use as a basic neuron in multi-state associative memories. The book is addressed to those readers who develop theoretical fundamentals of neural networks and use neural networks for solving various real-world problems. It should also be very suitable for Ph.D. and graduate students pursuing their degrees in computational intelligence.
Exploring Neural Networks With C
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Author : Ryszard Tadeusiewicz
language : en
Publisher: CRC Press
Release Date : 2017-07-27
Exploring Neural Networks With C written by Ryszard Tadeusiewicz and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-07-27 with Computers categories.
The utility of artificial neural network models lies in the fact that they can be used to infer functions from observations making them especially useful in applications where the complexity of data or tasks makes the design of such functions by hand impractical.Exploring Neural Networks with C# presents the important properties of neural networks
Human Centric Machine Vision
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Author : Fabio Solari
language : en
Publisher: BoD – Books on Demand
Release Date : 2012-05-02
Human Centric Machine Vision written by Fabio Solari and has been published by BoD – Books on Demand this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-05-02 with Computers categories.
Recently, the algorithms for the processing of the visual information have greatly evolved, providing efficient and effective solutions to cope with the variability and the complexity of real-world environments. These achievements yield to the development of Machine Vision systems that overcome the typical industrial applications, where the environments are controlled and the tasks are very specific, towards the use of innovative solutions to face with everyday needs of people. The Human-Centric Machine Vision can help to solve the problems raised by the needs of our society, e.g. security and safety, health care, medical imaging, and human machine interface. In such applications it is necessary to handle changing, unpredictable and complex situations, and to take care of the presence of humans.
Neural Network Computing For The Electric Power Industry
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Author : Dejan J. Sobajic
language : en
Publisher: Psychology Press
Release Date : 2013-06-17
Neural Network Computing For The Electric Power Industry written by Dejan J. Sobajic and has been published by Psychology Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-06-17 with Psychology categories.
Power system computing with neural networks is one of the fastest growing fields in the history of power system engineering. Since 1988, a considerable amount of work has been done in investigating computing capabilities of neural networks and understanding their relevance to providing efficient solutions for outstanding complex problems of the electric power industry. A principal objective of a power utility is to provide electric energy to its customers in a secure, reliable and economic manner. Toward this aim, utility personnel are engaged in a variety of activities in areas of supervisory control and monitoring, evaluation of operating conditions, operation planning and scheduling, system development, equipment testing, etc. Over the past decades significant advances have been made in the development of new concepts, design of hardware and software systems, and implementation of solid-state devices which all contributed to the steadily improving power system performance that we are experiencing today. Advanced information processing technologies played an important role in these development efforts. Members of the Special Interest Group for Power Engineering of the INNS recognized the need for bringing together leading researchers in the field of neurocomputing with experts from power utilities and manufacturing companies to assess the current state of affairs and to explore the directions of further research and practice. This book is based on The Summer Workshop on Neural Network Computing for the Electric Power Industry which brought together approximately forty specialists with backgrounds in power engineering, system operation and planning, neural network theory and AI systems design. An informal and highly inspiring atmosphere of the workshop facilitated open discussion and exchange of expertise between the participants.
Neural Networks With R
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Author : Giuseppe Ciaburro
language : en
Publisher: Packt Publishing Ltd
Release Date : 2017-09-27
Neural Networks With R written by Giuseppe Ciaburro and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-09-27 with Computers categories.
Uncover the power of artificial neural networks by implementing them through R code. About This Book Develop a strong background in neural networks with R, to implement them in your applications Build smart systems using the power of deep learning Real-world case studies to illustrate the power of neural network models Who This Book Is For This book is intended for anyone who has a statistical background with knowledge in R and wants to work with neural networks to get better results from complex data. If you are interested in artificial intelligence and deep learning and you want to level up, then this book is what you need! What You Will Learn Set up R packages for neural networks and deep learning Understand the core concepts of artificial neural networks Understand neurons, perceptrons, bias, weights, and activation functions Implement supervised and unsupervised machine learning in R for neural networks Predict and classify data automatically using neural networks Evaluate and fine-tune the models you build. In Detail Neural networks are one of the most fascinating machine learning models for solving complex computational problems efficiently. Neural networks are used to solve wide range of problems in different areas of AI and machine learning. This book explains the niche aspects of neural networking and provides you with foundation to get started with advanced topics. The book begins with neural network design using the neural net package, then you'll build a solid foundation knowledge of how a neural network learns from data, and the principles behind it. This book covers various types of neural network including recurrent neural networks and convoluted neural networks. You will not only learn how to train neural networks, but will also explore generalization of these networks. Later we will delve into combining different neural network models and work with the real-world use cases. By the end of this book, you will learn to implement neural network models in your applications with the help of practical examples in the book. Style and approach A step-by-step guide filled with real-world practical examples.
Neural Nets Wirn Vietri 96
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Author : Maria Marinaro
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06
Neural Nets Wirn Vietri 96 written by Maria Marinaro 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 2012-12-06 with Computers categories.
This volume contains selected papers from WIRN VIETRI-96, the 8th Italian Workshop on Neural Nets, held Vietri sul Mare, Salerno, Italy, from 23-25 May 1996. The papers cover a variety of topics related to neural networks, including pattern recognition, signal processing, theoretical models, applications in science and industry, virtual reality, fuzzy systems, and software algorithms. By providing the reader with a comprehensive overview of recent research work in this area, the volume makes an invaluable contribution to the Perspectives in Neural Computing Series. Neural Nets - WIRN VIETRI-96 will provide invaluable reading material for anyone who needs to keep up to date with the latest developments in neural networks and related areas. It will be of particular interest to academic and industrial researchers, and postgraduate and graduate students.