Download cellular neural networks and visual computing foundations and applications in pdf or read cellular neural networks and visual computing foundations and applications in pdf online books in PDF, EPUB and Mobi Format. Click Download or Read Online button to get cellular neural networks and visual computing foundations and applications in pdf book now. This site is like a library, Use search box in the widget to get ebook that you want.



Cellular Neural Networks And Visual Computing

Author: Leon O. Chua
Publisher: Cambridge University Press
ISBN: 9781139433327
Size: 15.12 MB
Format: PDF, Docs
View: 2747
Download and Read
Cellular Nonlinear/neural Network (CNN) technology is both a revolutionary concept and an experimentally proven new computing paradigm. Analogic cellular computers based on CNNs are set to change the way analog signals are processed and are paving the way to an analog computing industry. This unique undergraduate level textbook includes many examples and exercises, including CNN simulator and development software accessible via the Internet. It is an ideal introduction to CNNs and analogic cellular computing for students, researchers and engineers from a wide range of disciplines. Although its prime focus is on visual computing, the concepts and techniques described in the book will be of great interest to those working in other areas of research including modeling of biological, chemical and physical processes. Leon Chua, co-inventor of the CNN, and Tamás Roska are both highly respected pioneers in the field.

Single Neuron Computation

Author: Thomas M. McKenna
Publisher: Academic Press
ISBN: 1483296067
Size: 52.69 MB
Format: PDF, ePub, Docs
View: 3142
Download and Read
This book contains twenty-two original contributions that provide a comprehensive overview of computational approaches to understanding a single neuron structure. The focus on cellular-level processes is twofold. From a computational neuroscience perspective, a thorough understanding of the information processing performed by single neurons leads to an understanding of circuit- and systems-level activity. From the standpoint of artificial neural networks (ANNs), a single real neuron is as complex an operational unit as an entire ANN, and formalizing the complex computations performed by real neurons is essential to the design of enhanced processor elements for use in the next generation of ANNs. The book covers computation in dendrites and spines, computational aspects of ion channels, synapses, patterned discharge and multistate neurons, and stochastic models of neuron dynamics. It is the most up-to-date presentation of biophysical and computational methods.

Thinking In Complexity

Author: Klaus Mainzer
Publisher: Springer Science & Business Media
ISBN: 3540722289
Size: 33.25 MB
Format: PDF, Kindle
View: 6951
Download and Read
This new edition also treats smart materials and artificial life. A new chapter on information and computational dynamics takes up many recent discussions in the community.

Neural Networks For Applied Sciences And Engineering

Author: Sandhya Samarasinghe
Publisher: CRC Press
ISBN: 9781420013061
Size: 38.37 MB
Format: PDF
View: 7555
Download and Read
In response to the exponentially increasing need to analyze vast amounts of data, Neural Networks for Applied Sciences and Engineering: From Fundamentals to Complex Pattern Recognition provides scientists with a simple but systematic introduction to neural networks. Beginning with an introductory discussion on the role of neural networks in scientific data analysis, this book provides a solid foundation of basic neural network concepts. It contains an overview of neural network architectures for practical data analysis followed by extensive step-by-step coverage on linear networks, as well as, multi-layer perceptron for nonlinear prediction and classification explaining all stages of processing and model development illustrated through practical examples and case studies. Later chapters present an extensive coverage on Self Organizing Maps for nonlinear data clustering, recurrent networks for linear nonlinear time series forecasting, and other network types suitable for scientific data analysis. With an easy to understand format using extensive graphical illustrations and multidisciplinary scientific context, this book fills the gap in the market for neural networks for multi-dimensional scientific data, and relates neural networks to statistics. Features § Explains neural networks in a multi-disciplinary context § Uses extensive graphical illustrations to explain complex mathematical concepts for quick and easy understanding ? Examines in-depth neural networks for linear and nonlinear prediction, classification, clustering and forecasting § Illustrates all stages of model development and interpretation of results, including data preprocessing, data dimensionality reduction, input selection, model development and validation, model uncertainty assessment, sensitivity analyses on inputs, errors and model parameters Sandhya Samarasinghe obtained her MSc in Mechanical Engineering from Lumumba University in Russia and an MS and PhD in Engineering from Virginia Tech, USA. Her neural networks research focuses on theoretical understanding and advancements as well as practical implementations.

Universality And Emergent Computation In Cellular Neural Networks

Author: Radu Dogaru
Publisher: World Scientific
ISBN: 9812381023
Size: 10.71 MB
Format: PDF, ePub
View: 303
Download and Read
Cellular computing is a natural information processing paradigm, capable of modeling various biological, physical and social phenomena, as well as other kinds of complex adaptive systems. The programming of a cellular computer is in many respects similar to the genetic evolution in biology, the result being a proper cell design and a task-specific gene.How should one ?program? the cell of a cellular computer such that a dynamic behavior with computational relevance will emerge? What are the ?rules? for designing a computationally universal and efficient cell?The answers to those questions can be found in this book. It introduces the relatively new paradigm of the cellular neural network from an original perspective and provides the reader with the guidelines for understanding how such cellular computers can be ?programmed? and designed optimally. The book contains numerous practical examples and software simulators, allowing readers to experiment with the various phases of designing cellular computers by themselves.

Design And Implementation Of Intelligent Manufacturing Systems

Author: Mohammed Jamshidi
Publisher: Pearson Education
ISBN: 0132442078
Size: 14.46 MB
Format: PDF, Mobi
View: 4997
Download and Read
The introduction of artificial intelligence, neural networks, and fuzzy logic into industry has given a new perspective to manufacturing processes in the U.S. and abroad. To help readers keep pace, this book addresses topics of intelligent manufacturing from a variety of theoretical, empirical, design, and implementation perspectives.

Neural Information Processing And Vlsi

Author: Bing J. Sheu
Publisher: Springer Science & Business Media
ISBN: 1461522471
Size: 79.37 MB
Format: PDF, ePub, Mobi
View: 7237
Download and Read
Neural Information Processing and VLSI provides a unified treatment of this important subject for use in classrooms, industry, and research laboratories, in order to develop advanced artificial and biologically-inspired neural networks using compact analog and digital VLSI parallel processing techniques. Neural Information Processing and VLSI systematically presents various neural network paradigms, computing architectures, and the associated electronic/optical implementations using efficient VLSI design methodologies. Conventional digital machines cannot perform computationally-intensive tasks with satisfactory performance in such areas as intelligent perception, including visual and auditory signal processing, recognition, understanding, and logical reasoning (where the human being and even a small living animal can do a superb job). Recent research advances in artificial and biological neural networks have established an important foundation for high-performance information processing with more efficient use of computing resources. The secret lies in the design optimization at various levels of computing and communication of intelligent machines. Each neural network system consists of massively paralleled and distributed signal processors with every processor performing very simple operations, thus consuming little power. Large computational capabilities of these systems in the range of some hundred giga to several tera operations per second are derived from collectively parallel processing and efficient data routing, through well-structured interconnection networks. Deep-submicron very large-scale integration (VLSI) technologies can integrate tens of millions of transistors in a single silicon chip for complex signal processing and information manipulation. The book is suitable for those interested in efficient neurocomputing as well as those curious about neural network system applications. It has been especially prepared for use as a text for advanced undergraduate and first year graduate students, and is an excellent reference book for researchers and scientists working in the fields covered.

Autonomous Systems Developments And Trends

Author: Herwig Unger
Publisher: Springer
ISBN: 3642248063
Size: 22.82 MB
Format: PDF, ePub
View: 6135
Download and Read
The Workshops on Autonomous Systems emanated from a gathering with the doctoral students of just three chairs at Fernuniversität in Hagen, which we organise twice per year for a number of years now. Their purpose is to discuss on-going research and to create a community spirit. Furthermore, they serve as a means of structuring the students' research processes. The workshop has grown and matured in several respects. The doctoral students presenting their work do not come from a single university anymore, but from three. Besides them and their supervisors, also other scientists became interested in the event and contribute to its programme. Following the model of Advanced Study Institutes, they are available on the premises for relaxed, informal discussions outside the formal sessions. Finally, with the co-sponsorship of Gesellschaft für Informatik, the German Computer Society, and this surprisingly comprehensive volume of contributions published by Springer-Verlag the workshop turned into a visible scientific event.

Complex Valued Neural Networks

Author: Akira Hirose
Publisher: World Scientific
ISBN: 9812384642
Size: 53.13 MB
Format: PDF, ePub, Mobi
View: 3116
Download and Read
In recent years, complex-valued neural networks have widened the scope of application in optoelectronics, imaging, remote sensing, quantum neural devices and systems, spatiotemporal analysis of physiological neural systems, and artificial neural information processing. In this first-ever book on complex-valued neural networks, the most active scientists at the forefront of the field describe theories and applications from various points of view to provide academic and industrial researchers with a comprehensive understanding of the fundamentals, features and prospects of the powerful complex-valued networks.