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Non Linear Feedback Neural Networks

Author: Mohd. Samar Ansari
Publisher: Springer
ISBN: 813221563X
Size: 35.96 MB
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This book aims to present a viable alternative to the Hopfield Neural Network (HNN) model for analog computation. It is well known the standard HNN suffers from problems of convergence to local minima, and requirement of a large number of neurons and synaptic weights. Therefore, improved solutions are needed. The non-linear synapse neural network (NoSyNN) is one such possibility and is discussed in detail in this book. This book also discusses the applications in computationally intensive tasks like graph coloring, ranking, and linear as well as quadratic programming. The material in the book is useful to students, researchers and academician working in the area of analog computation.

Supervised And Unsupervised Pattern Recognition

Author: Evangelia Miche Tzanakou
Publisher: CRC Press
ISBN: 9781420049770
Size: 22.29 MB
Format: PDF
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There are many books on neural networks, some of which cover computational intelligence, but none that incorporate both feature extraction and computational intelligence, as Supervised and Unsupervised Pattern Recognition does. This volume describes the application of a novel, unsupervised pattern recognition scheme to the classification of various types of waveforms and images. This substantial collection of recent research begins with an introduction to Neural Networks, classifiers, and feature extraction methods. It then addresses unsupervised and fuzzy neural networks and their applications to handwritten character recognition and recognition of normal and abnormal visual evoked potentials. The third section deals with advanced neural network architectures-including modular design-and their applications to medicine and three-dimensional NN architecture simulating brain functions. The final section discusses general applications and simulations, such as the establishment of a brain-computer link, speaker identification, and face recognition. In the quickly changing field of computational intelligence, every discovery is significant. Supervised and Unsupervised Pattern Recognition gives you access to many notable findings in one convenient volume.

Artificial Neural Networks

Author: B. YEGNANARAYANA
Publisher: PHI Learning Pvt. Ltd.
ISBN: 9788120312531
Size: 64.51 MB
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Designed as an introductory level textbook on Artificial Neural Networks at the postgraduate and senior undergraduate levels in any branch of engineering, this self-contained and well-organized book highlights the need for new models of computing based on the fundamental principles of neural networks. Professor Yegnanarayana compresses, into the covers of a single volume, his several years of rich experience, in teaching and research in the areas of speech processing, image processing, artificial intelligence and neural networks. He gives a masterly analysis of such topics as Basics of artificial neural networks, Functional units of artificial neural networks for pattern recognition tasks, Feedforward and Feedback neural networks, and Archi-tectures for complex pattern recognition tasks. Throughout, the emphasis is on the pattern processing feature of the neural networks. Besides, the presentation of real-world applications provides a practical thrust to the discussion.

Encyclopedia Of Image Processing

Author: Phillip A. Laplante
Publisher: CRC Press
ISBN: 1351032739
Size: 18.49 MB
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The Encyclopedia of Image Processing presents a vast collection of well-written articles covering image processing fundamentals (e.g. color theory, fuzzy sets, cryptography) and applications (e.g. geographic information systems, traffic analysis, forgery detection). Image processing advances have enabled many applications in healthcare, avionics, robotics, natural resource discovery, and defense, which makes this text a key asset for both academic and industrial libraries and applied scientists and engineers working in any field that utilizes image processing. Written by experts from both academia and industry, it is structured using the ACM Computing Classification System (CCS) first published in 1988, but most recently updated in 2012.

Encyclopedia Of Biomaterials And Biomedical Engineering Second Edition

Author: Gary E. Wnek
Publisher: CRC Press
ISBN: 1498761437
Size: 44.56 MB
Format: PDF, Kindle
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Written by more than 400 subject experts representing diverse academic and applied domains, this multidisciplinary resource surveys the vanguard of biomaterials and biomedical engineering technologies utilizing biomaterials that lead to quality-of-life improvements. Building on traditional engineering principles, it serves to bridge advances in materials science, life sciences, nanotechnology, and cell biology to innovations in solving medical problems with applications in tissue engineering, prosthetics, drug delivery, biosensors, and medical devices. In nearly 300 entries, this four-volume Encyclopedia of Biomaterials and Biomedical Engineering, Second Edition covers: essential topics integral to tissue engineering research: bioreactors, scaffolding materials and fabrication, tissue mechanics, cellular interaction, and development of major tissues and organs being attempted by researchers worldwide artificial lungs and muscles, bio-artificial livers, and corneal, dental, inner ear, and total hip implants tissue engineering of blood vessels, heart valves, ligaments, microvascular networks, skeletal muscle, and skin bone remodeling, bone cement, and bioabsorbable bone plates and screws controlled drug delivery, insulin delivery, and transdermal and ocular implant-based drug delivery endovascular stent grafts, vascular grafts, and xenografts 3-D medical imaging, electrical impedance imaging, and intravascular ultrasound biomedical, protein adsorption, and in vivo cardiovascular modeling polymer foams, biofunctional and conductive polymers, and electroactive polymeric materials blood–material interactions, the bone–implant interface, host reactions, and foreign body responses and much more Also Available Online This Taylor & Francis encyclopedia is also available through online subscription, offering a variety of extra benefits for researchers, students, and librarians, including:  Citation tracking and alerts  Active reference linking  Saved searches and marked lists  HTML and PDF format options Contact Taylor and Francis for more information or to inquire about subscription options and print/online combination packages. US: (Tel) 1.888.318.2367; (E-mail) [email protected] International: (Tel) +44 (0) 20 7017 6062; (E-mail) [email protected]

Microcomputer Application In Process Control

Author: E. Adali
Publisher: Elsevier
ISBN: 1483298930
Size: 27.50 MB
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This symposium brings together the research from different disciplines of process control, and discusses the problems encountered in the application of automation systems. The papers in this volume analyze the results of theoretical research and how far applications have been developed, new design methodologies and technologies, to give a comprehensive overview of the state of the art of this fast-developing science.

Learning On Silicon

Author: G. Cauwenberghs
Publisher: Springer Science & Business Media
ISBN: 9780792385554
Size: 18.18 MB
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Learning on Silicon combines models of adaptive information processing in the brain with advances in microelectronics technology and circuit design. The premise is to construct integrated systems not only loaded with sufficient computational power to handle demanding signal processing tasks in sensory perception and pattern recognition, but also capable of operating autonomously and robustly in unpredictable environments through mechanisms of adaptation and learning. This edited volume covers the spectrum of Learning on Silicon in five parts: adaptive sensory systems, neuromorphic learning, learning architectures, learning dynamics, and learning systems. The 18 chapters are documented with examples of fabricated systems, experimental results from silicon, and integrated applications ranging from adaptive optics to biomedical instrumentation. As the first comprehensive treatment on the subject, Learning on Silicon serves as a reference for beginners and experienced researchers alike. It provides excellent material for an advanced course, and a source of inspiration for continued research towards building intelligent adaptive machines.