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Author : Martin T. Hagan
Publisher :
ISBN 13 : 9789812403766
Total Pages : pages
Book Rating : 4.4/5 (37 download)
Download or read book Neural Network Design written by Martin T. Hagan and published by . This book was released on 2003 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Sun Yuan Kung
Publisher : Prentice Hall
ISBN 13 :
Total Pages : 472 pages
Book Rating : 4.3/5 (91 download)
Download or read book Digital Neural Networks written by Sun Yuan Kung and published by Prentice Hall. This book was released on 1993 with total page 472 pages. Available in PDF, EPUB and Kindle. Book excerpt: Intended for engineers and researchers interested in the applications of neural networks to signal and image processing, this book is theoretically based with emphasis on application and implementation. Coverage includes neural networks for representation, unsupervised networks for association/classification, neural networks for generalization/restoration, neural net and conventional optimization techniques, and special purpose supercomputers for neural nets.
Author : Munish Puri
Publisher : Academic Press
ISBN 13 : 0128017449
Total Pages : 442 pages
Book Rating : 4.1/5 (28 download)
Download or read book Artificial Neural Network for Drug Design, Delivery and Disposition written by Munish Puri and published by Academic Press. This book was released on 2015-10-15 with total page 442 pages. Available in PDF, EPUB and Kindle. Book excerpt: Artificial Neural Network for Drug Design, Delivery and Disposition provides an in-depth look at the use of artificial neural networks (ANN) in pharmaceutical research. With its ability to learn and self-correct in a highly complex environment, this predictive tool has tremendous potential to help researchers more effectively design, develop, and deliver successful drugs. This book illustrates how to use ANN methodologies and models with the intent to treat diseases like breast cancer, cardiac disease, and more. It contains the latest cutting-edge research, an analysis of the benefits of ANN, and relevant industry examples. As such, this book is an essential resource for academic and industry researchers across the pharmaceutical and biomedical sciences. - Written by leading academic and industry scientists who have contributed significantly to the field and are at the forefront of artificial neural network (ANN) research - Focuses on ANN in drug design, discovery and delivery, as well as adopted methodologies and their applications to the treatment of various diseases and disorders - Chapters cover important topics across the pharmaceutical process, such as ANN in structure-based drug design and the application of ANN in modern drug discovery - Presents the future potential of ANN-based strategies in biomedical image analysis and much more
Author : Yoshiyasu Takefuji
Publisher : World Scientific
ISBN 13 : 9814504564
Total Pages : 319 pages
Book Rating : 4.8/5 (145 download)
Download or read book Neural Networks In Design And Manufacturing written by Yoshiyasu Takefuji and published by World Scientific. This book was released on 1993-10-29 with total page 319 pages. Available in PDF, EPUB and Kindle. Book excerpt: Over the past few years, there has been a surge of research activities on artificial neural networks. Although the thrust originally came from computer scientists and electrical engineers, neural network research has recently attracted researchers in the fields of operations research, operations management and industrial engineering.Despite the huge volume of recent publications devoted to neural network research, there is no single monograph addressing the potential roles of artificial neural networks for design and manufacturing.The focus of this book is on the applications of neural network concepts and techniques to design and manufacturing. This book reviews the state-of-the-art of the research activities, highlights the recent advances in research and development, and discusses the potential directions and future trends along this stream of research.The potential readers of this book will include, but are not limited to, beginners, professionals and practitioners in industries who are applying neural networks to design and manufacturing.The topics include conceptual design, group technology, process planning and scheduling, process monitoring and others.
Author : Věra Kůrková
Publisher : Springer Science & Business Media
ISBN 13 : 3540875581
Total Pages : 1012 pages
Book Rating : 4.5/5 (48 download)
Download or read book Artificial Neural Networks - ICANN 2008 written by Věra Kůrková and published by Springer Science & Business Media. This book was released on 2008 with total page 1012 pages. Available in PDF, EPUB and Kindle. Book excerpt: This two volume set LNCS 5163 and LNCS 5164 constitutes the refereed proceedings of the 18th International Conference on Artificial Neural Networks, ICANN 2008, held in Prague Czech Republic, in September 2008. The 200 revised full papers presented were carefully reviewed and selected from more than 300 submissions. The second volume is devoted to pattern recognition and data analysis, hardware and embedded systems, computational neuroscience, connectionistic cognitive science, neuroinformatics and neural dynamics. it also contains papers from two special sessions coupling, synchronies, and firing patterns: from cognition to disease, and constructive neural networks and two workshops new trends in self-organization and optimization of artificial neural networks, and adaptive mechanisms of the perception-action cycle.
Author : Sankar K. Pal
Publisher : World Scientific
ISBN 13 : 981277808X
Total Pages : 421 pages
Book Rating : 4.8/5 (127 download)
Download or read book Neural Networks and Systolic Array Design written by Sankar K. Pal and published by World Scientific. This book was released on 2002 with total page 421 pages. Available in PDF, EPUB and Kindle. Book excerpt: Neural networks (NNs) and systolic arrays (SAs) have many similar features. This volume describes, in a unified way, the basic concepts, theories and characteristic features of integrating or formulating different facets of NNs and SAs, as well as presents recent developments and significant applications. The articles, written by experts from all over the world, demonstrate the various ways this integration can be made to efficiently design methodologies, algorithms and architectures, and also implementations, for NN applications. The book will be useful to graduate students and researchers in many related areas, not only as a reference book but also as a textbook for some parts of the curriculum. It will also benefit researchers and practitioners in industry and R&D laboratories who are working in the fields of system design, VLSI, parallel processing, neural networks, and vision.
Author : Amos R. Omondi
Publisher : Springer Science & Business Media
ISBN 13 : 0387284877
Total Pages : 365 pages
Book Rating : 4.3/5 (872 download)
Download or read book FPGA Implementations of Neural Networks written by Amos R. Omondi and published by Springer Science & Business Media. This book was released on 2006-10-04 with total page 365 pages. Available in PDF, EPUB and Kindle. Book excerpt: During the 1980s and early 1990s there was signi?cant work in the design and implementation of hardware neurocomputers. Nevertheless, most of these efforts may be judged to have been unsuccessful: at no time have have ha- ware neurocomputers been in wide use. This lack of success may be largely attributed to the fact that earlier work was almost entirely aimed at developing custom neurocomputers, based on ASIC technology, but for such niche - eas this technology was never suf?ciently developed or competitive enough to justify large-scale adoption. On the other hand, gate-arrays of the period m- tioned were never large enough nor fast enough for serious arti?cial-neur- network (ANN) applications. But technology has now improved: the capacity and performance of current FPGAs are such that they present a much more realistic alternative. Consequently neurocomputers based on FPGAs are now a much more practical proposition than they have been in the past. This book summarizes some work towards this goal and consists of 12 papers that were selected, after review, from a number of submissions. The book is nominally divided into three parts: Chapters 1 through 4 deal with foundational issues; Chapters 5 through 11 deal with a variety of implementations; and Chapter 12 looks at the lessons learned from a large-scale project and also reconsiders design issues in light of current and future technology.
Author : Joan Cabestany
Publisher : Springer Science & Business Media
ISBN 13 : 3540262083
Total Pages : 1282 pages
Book Rating : 4.5/5 (42 download)
Download or read book Eighth International Work-Conference on Artificial and Natural Neural Networks written by Joan Cabestany and published by Springer Science & Business Media. This book was released on 2005-05-30 with total page 1282 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Author : Xingui He
Publisher : Springer Science & Business Media
ISBN 13 : 3540737626
Total Pages : 240 pages
Book Rating : 4.5/5 (47 download)
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.
Author : Nibaran Das
Publisher : Springer Nature
ISBN 13 : 9819764890
Total Pages : 407 pages
Book Rating : 4.8/5 (197 download)
Download or read book Proceedings of International Conference on Data, Electronics and Computing written by Nibaran Das and published by Springer Nature. This book was released on with total page 407 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Zhang, Ming
Publisher : IGI Global
ISBN 13 : 1466621761
Total Pages : 455 pages
Book Rating : 4.4/5 (666 download)
Download or read book Artificial Higher Order Neural Networks for Modeling and Simulation written by Zhang, Ming and published by IGI Global. This book was released on 2012-10-31 with total page 455 pages. Available in PDF, EPUB and Kindle. Book excerpt: "This book introduces Higher Order Neural Networks (HONNs) to computer scientists and computer engineers as an open box neural networks tool when compared to traditional artificial neural networks"--Provided by publisher.
Author : Alma Y Alanis
Publisher : Academic Press
ISBN 13 : 0128182474
Total Pages : 176 pages
Book Rating : 4.1/5 (281 download)
Download or read book Artificial Neural Networks for Engineering Applications written by Alma Y Alanis and published by Academic Press. This book was released on 2019-02-13 with total page 176 pages. Available in PDF, EPUB and Kindle. Book excerpt: Artificial Neural Networks for Engineering Applications presents current trends for the solution of complex engineering problems that cannot be solved through conventional methods. The proposed methodologies can be applied to modeling, pattern recognition, classification, forecasting, estimation, and more. Readers will find different methodologies to solve various problems, including complex nonlinear systems, cellular computational networks, waste water treatment, attack detection on cyber-physical systems, control of UAVs, biomechanical and biomedical systems, time series forecasting, biofuels, and more. Besides the real-time implementations, the book contains all the theory required to use the proposed methodologies for different applications.
Author : Nan Zheng
Publisher : John Wiley & Sons
ISBN 13 : 1119507391
Total Pages : 300 pages
Book Rating : 4.1/5 (195 download)
Download or read book Learning in Energy-Efficient Neuromorphic Computing: Algorithm and Architecture Co-Design written by Nan Zheng and published by John Wiley & Sons. This book was released on 2019-10-18 with total page 300 pages. Available in PDF, EPUB and Kindle. Book excerpt: Explains current co-design and co-optimization methodologies for building hardware neural networks and algorithms for machine learning applications This book focuses on how to build energy-efficient hardware for neural networks with learning capabilities—and provides co-design and co-optimization methodologies for building hardware neural networks that can learn. Presenting a complete picture from high-level algorithm to low-level implementation details, Learning in Energy-Efficient Neuromorphic Computing: Algorithm and Architecture Co-Design also covers many fundamentals and essentials in neural networks (e.g., deep learning), as well as hardware implementation of neural networks. The book begins with an overview of neural networks. It then discusses algorithms for utilizing and training rate-based artificial neural networks. Next comes an introduction to various options for executing neural networks, ranging from general-purpose processors to specialized hardware, from digital accelerator to analog accelerator. A design example on building energy-efficient accelerator for adaptive dynamic programming with neural networks is also presented. An examination of fundamental concepts and popular learning algorithms for spiking neural networks follows that, along with a look at the hardware for spiking neural networks. Then comes a chapter offering readers three design examples (two of which are based on conventional CMOS, and one on emerging nanotechnology) to implement the learning algorithm found in the previous chapter. The book concludes with an outlook on the future of neural network hardware. Includes cross-layer survey of hardware accelerators for neuromorphic algorithms Covers the co-design of architecture and algorithms with emerging devices for much-improved computing efficiency Focuses on the co-design of algorithms and hardware, which is especially critical for using emerging devices, such as traditional memristors or diffusive memristors, for neuromorphic computing Learning in Energy-Efficient Neuromorphic Computing: Algorithm and Architecture Co-Design is an ideal resource for researchers, scientists, software engineers, and hardware engineers dealing with the ever-increasing requirement on power consumption and response time. It is also excellent for teaching and training undergraduate and graduate students about the latest generation neural networks with powerful learning capabilities.
Author : Leszek Rutkowski
Publisher : Springer
ISBN 13 : 3319912534
Total Pages : 796 pages
Book Rating : 4.3/5 (199 download)
Download or read book Artificial Intelligence and Soft Computing written by Leszek Rutkowski and published by Springer. This book was released on 2018-05-24 with total page 796 pages. Available in PDF, EPUB and Kindle. Book excerpt: The two-volume set LNAI 10841 and LNAI 10842 constitutes the refereed proceedings of the 17th International Conference on Artificial Intelligence and Soft Computing, ICAISC 2018, held in Zakopane, Poland in June 2018. The 140 revised full papers presented were carefully reviewed and selected from 242 submissions. The papers included in the first volume are organized in the following three parts: neural networks and their applications; evolutionary algorithms and their applications; and pattern classification.
Author : O.V. Gnana Swathika
Publisher : CRC Press
ISBN 13 : 1000909778
Total Pages : 335 pages
Book Rating : 4.0/5 (9 download)
Download or read book IoT and Analytics in Renewable Energy Systems (Volume 1) written by O.V. Gnana Swathika and published by CRC Press. This book was released on 2023-08-11 with total page 335 pages. Available in PDF, EPUB and Kindle. Book excerpt: Smart grid technologies include sensing and measurement technologies, advanced components aided with communications and control methods along with improved interfaces and decision support systems. Smart grid techniques support the extensive inclusion of clean renewable generation in power systems. Smart grid use also promotes energy saving in power systems. Cyber security objectives for the smart grid are availability, integrity and confidentiality. Five salient features of this book are as follows: AI and IoT in improving resilience of smart energy infrastructure IoT, smart grids and renewable energy: an economic approach AI and ML towards sustainable solar energy Electrical vehicles and smart grid Intelligent condition monitoring for solar and wind energy systems
Author : Daniel Graupe
Publisher : World Scientific
ISBN 13 : 9814475564
Total Pages : 320 pages
Book Rating : 4.8/5 (144 download)
Download or read book Principles Of Artificial Neural Networks (2nd Edition) written by Daniel Graupe and published by World Scientific. This book was released on 2007-04-05 with total page 320 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book should serve as a text for a university graduate course or for an advanced undergraduate course on neural networks in engineering and computer science departments. It should also serve as a self-study course for engineers and computer scientists in the industry. Covering major neural network approaches and architectures with the theories, this text presents detailed case studies for each of the approaches, accompanied with complete computer codes and the corresponding computed results. The case studies are designed to allow easy comparison of network performance to illustrate strengths and weaknesses of the different networks.
Author : M A Hussain
Publisher : World Scientific
ISBN 13 : 178326148X
Total Pages : 423 pages
Book Rating : 4.7/5 (832 download)
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.
