Evolution of Networks: From Biological Nets to the Internet and WWW, Dorogovtsev S. N., Mendes J. F. F.

Автор: HrГєz Branislav, Zhou MengChu
Название: Modeling and Control of Discrete-event Dynamic Systems / with Petri Nets and Other Tools
ISBN: 184628872X ISBN-13(EAN): 9781846288722
Издательство: Springer
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Цена: 72710 T
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Описание: Discrete-event dynamic systems (DEDs) permeate our world, being of great importance in modern manufacturing processes, transportation and various forms of computer and communications networking.Realistic industrial examples of varying complexity illustrate the concepts and methods under discussion. Using them, readers will be able to understand DEDs quickly and to master the control methods to analyze and improve the performance of their systems.Final-year undergraduates and graduates embarking on further courses of study in control, manufacturing and process engineering, computer studies or operations research will find Modeling and Control of Discrete-event Dynamic Systems an invaluable companion to learning about the control of this increasingly important class of systems.

Автор: Haas Peter J.
Название: Stochastic Petri Nets / Modelling, Stability, Simulation
ISBN: 0387954457 ISBN-13(EAN): 9780387954455
Издательство: Springer
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Цена: 103890 T
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Описание: Stochastic petri nets have proven to be a useful tool for modelling and performance analysis of complex discrete-event stochastic systems such as those in telecommunications, manufacturing, transportation. This monograph centers on techniques for the modelling and computer simulation of such systems. Researchers and graduate students in applied math, computer engineering, computer science, electrical engineering, industrial engineering operations research and applied probability will find this book useful.

Автор: Swishchuk A., Jianhong Wu
Название: Evolution of Biological Systems in Random Media: Limit Theorems and Stability
ISBN: 1402015542 ISBN-13(EAN): 9781402015540
Издательство: Springer
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Цена: 115490 T
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Описание: This is a new book in biomathematics, which includes new models of stochastic non-linear biological systems and new results for these systems. These results are based on the new results for non-linear difference and differential equations in random media. This book contains: -New stochastic non-linear models of biological systems, such as biological systems in random media: epidemic, genetic selection, demography, branching, logistic growth and predator-prey models; -New results for scalar and vector difference equations in random media with applications to the stochastic biological systems in 1); -New results for stochastic non-linear biological systems, such as averaging, merging, diffusion approximation, normal deviations and stability; -New approach to the study of stochastic biological systems in random media such as random evolution approach.

Автор: Mastebroek H.A., Vos J.E.
Название: Plausible Neural Networks for Biological Modelling
ISBN: 0792371925 ISBN-13(EAN): 9780792371922
Издательство: Springer
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Цена: 161690 T
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Описание: This book has the unique intention of returning the mathematical tools of neural networks to the biological realm of the nervous system, where they originated a few decades ago. It aims to introduce, in a didactic manner, two relatively recent developments in neural network methodology, namely recurrence in the architecture and the use of spiking or integrate-and-fire neurons. In addition, the neuro-anatomical processes of synapse modification during development, training, and memory formation are discussed as realistic bases for weight-adjustment in neural networks. While neural networks have many applications outside biology, where it is irrelevant precisely which architecture and which algorithms are used, it is essential that there is a close relationship between the network's properties and whatever is the case in a neuro-biological phenomenon that is being modelled or simulated in terms of a neural network. A recurrent architecture, the use of spiking neurons and appropriate weight update rules contribute to the plausibility of a neural network in such a case. Therefore, in the first half of this book the foundations are laid for the application of neural networks as models for the various biological phenomena that are treated in the second half of this book. These include various neural network models of sensory and motor control tasks that implement one or several of the requirements for biological plausibility.

Автор: Corten
Название: Computational Approaches to Studying the Co-evolution of Networks and Behavior in Social Dilemmas
ISBN: 1118636872 ISBN-13(EAN): 9781118636879
Издательство: Wiley
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Цена: 81470 T
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Описание: Computational Approaches to Studying the Co-evolution of Networks and Behaviour in Social Dilemmas shows students, researchers, and professionals how to use computation methods, rather than mathematical analysis, to answer research questions for an easier, more productive method of testing their models.

Автор: Haken Hermann
Название: Synergetic Computers and Cognition / A Top-Down Approach to Neural Nets
ISBN: 3540421637 ISBN-13(EAN): 9783540421634
Издательство: Springer
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Цена: 92340 T
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Описание: This book presents a novel approach to neural nets and thus offers a genuine alternative to the hitherto known neuro-computers. This approach is based on the author's discovery of the profound analogy between pattern recognition and pattern formation in open systems far from equilibrium. Thus the mathematical and conceptual tools of synergetics can be exploited, and the concept of the synergetic computer formulated. A complete and rigorous theory of pattern recognition and learning is presented. The resulting algorithm can be implemented on serial computers or realized by fully parallel nets whereby no spurious states occur. Explicit examples (e.g. recognition of faces and city maps) are provided. The recognition process is made invariant with respect to simultaneous translation, rotation, and scaling, and allows the recognition of complex scenes. Oscillations and hysteresis in the perception of ambiguous patterns are treated, as well as the recognition of movement patterns. A comparison between the recognition abilities of humans and the synergetic computer sheds new light on possible models of mental processes. The synergetic computer can also perform logical steps such as the XOR operation. The new edition includes a section on transformation properties of the equations of the synergetic computer and on the invariance properties of the order parameter equations. Further additions are a new section on stereopsis and recent developments in the use of pulse-coupled neural nets for pattern recognition.

Автор: Reinhard German
Название: Performance Analysis of Communication Systems : Modeling with Non-Markovian Stochastic Petri Nets
ISBN: 0471492582 ISBN-13(EAN): 9780471492580
Издательство: Wiley
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Цена: 247500 T
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Описание: Petri nets are used for modelling systems with concurrency such as traffic flow within communication systems. Stochastic petri nets have become popular for the model description of tools used for performance analysis. Introducing the analysis techniques and algorithms used in performance evaluation with non-Markovian stochastic petri nets, this volume takes a systematic approach with clear presentation. Each definition, concept and algorithm presented is accompanied by an example to clarify its use.

Автор: Haken Hermann
Название: Brain Dynamics / Synchronization and Activity Patterns in Pulse-Coupled Neural Nets with Delays and Noise
ISBN: 3540462821 ISBN-13(EAN): 9783540462828
Издательство: Springer
Цена: 57690 T
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Описание: This book addresses a large variety of models in mathematical and computational neuroscience. It is written for the experts as well as for graduate students wishing to enter this fascinating field of research. The author studies the behaviour of large neural networks composed of many neurons coupled by spike trains. He devotes the main part to the synchronization problem. He presents neural net models more realistic than the conventional ones by taking into account the detailed dynamics of axons, synapses and dendrites, allowing rather arbitrary couplings between neurons. He gives a complete stabile analysis that goes significantly beyond what has been known so far. He also derives pulse-averaged equations including those of the Wilson-Cowan and the Jirsa-Haken-Nunez types and discusses the formation of spatio-temporal neuronal activity pattems. An analysis of phase locking via sinusoidal couplings leading to various kinds of movement coordination is included.

Автор: David RenГ©, Alla Hassane
Название: Discrete, Continuous, and Hybrid Petri Nets
ISBN: 3540224807 ISBN-13(EAN): 9783540224808
Издательство: Springer
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Цена: 138540 T
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Описание: This monograph presents a well written and clearly organized introduction in the standard methods of discrete, continuous and hybrid Petri Nets. Starting from the basics of Petri Nets the book imparts an accurate understanding of continuous and hybrid Petri Nets. Preserving the consistency of basic concepts throughout the text it introduces a unified framework for all the models presented. The book is a scientific monograph as well as a didactic tutorial which is easy to understand due to many exercises with solutions, detailed figures and several case studies. It demonstrates that Petri nets are a deep, practical and alive field important for researchers, engineers and graduate students in engineering and computer science.

Автор: Deutsch, A.; Bravo de la Parra, R.; de Boer, R.J.; Diekmann, O.; Jagers, P.; Kisdi, E.; Kretzschmar, M.; Lansky, P.; Metz, H. (Eds.)
Название: Mathematical Modeling of Biological Systems, Volume II Epidemiology, Evolution and Ecology, Immunology, Neural Systems and the Brain, and Innovative Mathematical Methods
ISBN: 0817645551 ISBN-13(EAN): 9780817645557
Издательство: Springer
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Цена: 150140 T
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Описание: Presents a broad range of topics in the field of mathematical modeling in the biological sciences. This work examines the central problems in the life sciences, ranging from the organizational principles of individual cells to the dynamics of large populations.

Автор: Deutsch, A.; Brusch, L.; Byrne, H.; de Vries, G.; Herzel, H. (Eds.)
Название: Mathematical Modeling of Biological Systems, Volume I Cellular Biophysics, Regulatory Networks, Development, Biomedicine, and Data Analysis
ISBN: 0817645578 ISBN-13(EAN): 9780817645571
Издательство: Springer
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Цена: 150140 T
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Описание: This edited volume contains a selection of chapters that are an outgrowth of the - ropean Conference on Mathematical and Theoretical Biology (ECMTB05, Dresden, Germany, July 2005). The peer-reviewed contributions show that mathematical and computational approaches are absolutely essential for solving central problems in the life sciences, ranging from the organizational level of individual cells to the dynamics of whole populations. The contributions indicate that theoretical and mathematical biology is a diverse and interdisciplinary ?eld, ranging from experimental research linked to mathema- cal modeling to the development of more abstract mathematical frameworks in which observations about the real world can be interpreted, and with which new hypotheses for testing can be generated. Today, much attention is also paid to the development of ef?cient algorithms for complex computation and visualisation, notably in molecular biology and genetics. The ?eld of theoretical and mathematical biology and medicine has profound connections to many current problems of great relevance to society. The medical, industrial, and social interests in its development are in fact indisputable.

Автор: Harris C J & Moore C G & Brown M
Название: Intelligent Control: Aspects Of Fuzzy Logic And Neural Nets
ISBN: 9810210426 ISBN-13(EAN): 9789810210427
Издательство: World Scientific Publishing
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Цена: 112300 T
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Описание: With increasing demands for high precision autonomous control over wide operating envelopes, conventional control engineering approaches are unable to adequately deal with system complexity, nonlinearities, spatial and temporal parameter variations, and with uncertainty. Intelligent Control or self-organising/learning control is a new emerging discipline that is designed to deal with problems. Rather than being model based, it is experiential based. Intelligent Control is the amalgam of the disciplines of Artificial Intelligence, Systems Theory and Operations Research. It uses most recent experiences or evidence to improve its performance through a variety of learning schemas, that for practical implementation must demonstrate rapid learning convergence, be temporally stable, be robust to parameter changes and internal and external disturbances. It is shown in this book that a wide class of fuzzy logic and neural net based learning algorithms satisfy these conditions. It is demonstrated that this class of intelligent controllers is based upon a fixed nonlinear mapping of the input (sensor) vector, followed by an output layer linear mapping with coefficients that are updated by various first order learning laws. Under these conditions self-organising fuzzy logic controllers and neural net controllers have common learning attributes.A theme example of the navigation and control of an autonomous guided vehicle is included throughout, together with a series of bench examples to demonstrate this new theory and its applicability.