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Book Control and Dynamic Systems

Download or read book Control and Dynamic Systems written by and published by . This book was released on 1967 with total page 448 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book Neural Networks in Business

Download or read book Neural Networks in Business written by Kate A. Smith and published by IGI Global. This book was released on 2003-01-01 with total page 274 pages. Available in PDF, EPUB and Kindle. Book excerpt: "For professionals, students, and academics interested in applying neural networks to a variety of business applications, this reference book introduces the three most common neural network models and how they work. A wide range of business applications and a series of global case studies are presented to illustrate the neural network models provided. Each model or technique is discussed in detail and used to solve a business problem such as managing direct marketing, calculating foreign exchange rates, and improving cash flow forecasting."

Book Neural Networks

    Book Details:
  • Author : Gérard Dreyfus
  • Publisher : Springer Science & Business Media
  • Release : 2005-11-25
  • ISBN : 3540288473
  • Pages : 509 pages

Download or read book Neural Networks written by Gérard Dreyfus and published by Springer Science & Business Media. This book was released on 2005-11-25 with total page 509 pages. Available in PDF, EPUB and Kindle. Book excerpt: Neural networks represent a powerful data processing technique that has reached maturity and broad application. When clearly understood and appropriately used, they are a mandatory component in the toolbox of any engineer who wants make the best use of the available data, in order to build models, make predictions, mine data, recognize shapes or signals, etc. Ranging from theoretical foundations to real-life applications, this book is intended to provide engineers and researchers with clear methodologies for taking advantage of neural networks in industrial, financial or banking applications, many instances of which are presented in the book. For the benefit of readers wishing to gain deeper knowledge of the topics, the book features appendices that provide theoretical details for greater insight, and algorithmic details for efficient programming and implementation. The chapters have been written by experts and edited to present a coherent and comprehensive, yet not redundant, practically oriented introduction.

Book Neural Network Systems Techniques and Applications

Download or read book Neural Network Systems Techniques and Applications written by and published by Academic Press. This book was released on 1998-02-09 with total page 459 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book emphasizes neural network structures for achieving practical and effective systems, and provides many examples. Practitioners, researchers, and students in industrial, manufacturing, electrical, mechanical,and production engineering will find this volume a unique and comprehensive reference source for diverse application methodologies. Control and Dynamic Systems covers the important topics of highly effective Orthogonal Activation Function Based Neural Network System Architecture, multi-layer recurrent neural networks for synthesizing and implementing real-time linear control,adaptive control of unknown nonlinear dynamical systems, Optimal Tracking Neural Controller techniques, a consideration of unified approximation theory and applications, techniques for the determination of multi-variable nonlinear model structures for dynamic systems with a detailed treatment of relevant system model input determination, High Order Neural Networks and Recurrent High Order Neural Networks, High Order Moment Neural Array Systems, Online Learning Neural Network controllers, and Radial Bias Function techniques. Coverage includes: Orthogonal Activation Function Based Neural Network System Architecture (OAFNN) Multilayer recurrent neural networks for synthesizing and implementing real-time linear control Adaptive control of unknown nonlinear dynamical systems Optimal Tracking Neural Controller techniques Consideration of unified approximation theory and applications Techniques for determining multivariable nonlinear model structures for dynamic systems, with a detailed treatment of relevant system model input determination

Book Process Neural Networks

    Book Details:
  • Author : Xingui He
  • Publisher : Springer Science & Business Media
  • Release : 2010-07-05
  • ISBN : 3540737626
  • Pages : 240 pages

Download or read book Process Neural Networks written by Xingui He and published by Springer Science & Business Media. This book was released on 2010-07-05 with total page 240 pages. Available in PDF, EPUB and Kindle. Book excerpt: For the first time, this book sets forth the concept and model for a process neural network. You’ll discover how a process neural network expands the mapping relationship between the input and output of traditional neural networks and greatly enhances the expression capability of artificial neural networks. Detailed illustrations help you visualize information processing flow and the mapping relationship between inputs and outputs.

Book Neural Networks and Their Applications

Download or read book Neural Networks and Their Applications written by John G. Taylor and published by John Wiley & Sons. This book was released on 1996 with total page 336 pages. Available in PDF, EPUB and Kindle. Book excerpt: Neural networks are one of the fast-growing paradigms for learning systems with a wide variety of potential applications in industry. In particular there are general results which prove the universal applicability of neural networks to many problems. There is also an ever greater understanding of the underlying manner in which tasks such as classification can be solved optimally by this host of techniques. Through the application of ideas of statistics, dynamical systems theory and information theory the methods are likely to become ever more effective for solving problems previously found to be difficult to tackle using standard techniques. This book compares and contrasts the academic theory and the industrial reality, with case studies and latest research findings from international experts. The contributions describe application areas including finance, digital data transmission, hybrid systems, automotive and aerospace industries, pattern analysis in clinical psychiatry, time series prediction, and genetic and neural algorithms. This book demonstrates the vigour and strength of the subject in solving hard problems and as such will be of great interest to all researchers and professionals with an interest in neural networks.

Book Neural Networks  Computational Models and Applications

Download or read book Neural Networks Computational Models and Applications written by Huajin Tang and published by Springer Science & Business Media. This book was released on 2007-03-12 with total page 310 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Book Neural Network Applications in Control

Download or read book Neural Network Applications in Control written by George William Irwin and published by IET. This book was released on 1995 with total page 320 pages. Available in PDF, EPUB and Kindle. Book excerpt: The aim is to present an introduction to, and an overview of, the present state of neural network research and development, with an emphasis on control systems application studies. The book is useful to a range of levels of reader. The earlier chapters introduce the more popular networks and the fundamental control principles, these are followed by a series of application studies, most of which are industrially based, and the book concludes with a consideration of some recent research.

Book State of the Art in Neural Networks and Their Applications

Download or read book State of the Art in Neural Networks and Their Applications written by Ayman S. El-Baz and published by Academic Press. This book was released on 2021-07-21 with total page 326 pages. Available in PDF, EPUB and Kindle. Book excerpt: State of the Art in Neural Networks and Their Applications presents the latest advances in artificial neural networks and their applications across a wide range of clinical diagnoses. Advances in the role of machine learning, artificial intelligence, deep learning, cognitive image processing and suitable data analytics useful for clinical diagnosis and research applications are covered, including relevant case studies. The application of Neural Network, Artificial Intelligence, and Machine Learning methods in biomedical image analysis have resulted in the development of computer-aided diagnostic (CAD) systems that aim towards the automatic early detection of several severe diseases. State of the Art in Neural Networks and Their Applications is presented in two volumes. Volume 1 covers the state-of-the-art deep learning approaches for the detection of renal, retinal, breast, skin, and dental abnormalities and more. Includes applications of neural networks, AI, machine learning, and deep learning techniques to a variety of imaging technologies Provides in-depth technical coverage of computer-aided diagnosis (CAD), with coverage of computer-aided classification, Unified Deep Learning Frameworks, mammography, fundus imaging, optical coherence tomography, cryo-electron tomography, 3D MRI, CT, and more Covers deep learning for several medical conditions including renal, retinal, breast, skin, and dental abnormalities, Medical Image Analysis, as well as detection, segmentation, and classification via AI

Book Application Of Neural Networks And Other Learning Technologies In Process Engineering

Download or read book Application Of Neural Networks And Other Learning Technologies In Process Engineering written by M A Hussain and published by World Scientific. This book was released on 2001-04-02 with total page 423 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is a follow-up to the IChemE symposium on “Neural Networks and Other Learning Technologies”, held at Imperial College, UK, in May 1999. The interest shown by the participants, especially those from the industry, has been instrumental in producing the book. The papers have been written by contributors of the symposium and experts in this field from around the world. They present all the important aspects of neural network utilisation as well as show the versatility of neural networks in various aspects of process engineering problems — modelling, estimation, control, optimisation and industrial applications.

Book Artificial Higher Order Neural Networks for Computer Science and Engineering  Trends for Emerging Applications

Download or read book Artificial Higher Order Neural Networks for Computer Science and Engineering Trends for Emerging Applications written by Zhang, Ming and published by IGI Global. This book was released on 2010-02-28 with total page 660 pages. Available in PDF, EPUB and Kindle. Book excerpt: "This book introduces and explains Higher Order Neural Networks (HONNs) to people working in the fields of computer science and computer engineering, and how to use HONNS in these areas"--Provided by publisher.

Book Neural Network Systems Techniques and Applications  Seven Volume Set

Download or read book Neural Network Systems Techniques and Applications Seven Volume Set written by Cornelius T. Leondes and published by Academic Press. This book was released on 1998-02-11 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Artificial neural networks have been widely applied to many fields--such as pattern recognition, optimization, coding, and control--due to their capability of solving cumbersome or intractable problems by learning directly from data. Neural networks adapt to new environments and deal with information that is noisy, inconsistent, vague, or probabilistic. These features have motivated extensive research and developments in artificial neural networks. A unique and comprehensive reference, this Series covers the different techniques, applications, and systems of artificial neural networks. It will be a valuable and powerful resource for a wide array of practitioners, researchers, and students, including those in the fields of industrial, manufacturing, electrical, and mechanical engineering, as well as computer science and engineering.