Pulsed Neural Networks

Pulsed Neural Networks

Author: Wolfgang Maass

Publisher: MIT Press

Published: 2001-01-26

Total Pages: 414

ISBN-13: 9780262632218

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Most practical applications of artificial neural networks are based on a computational model involving the propagation of continuous variables from one processing unit to the next. In recent years, data from neurobiological experiments have made it increasingly clear that biological neural networks, which communicate through pulses, use the timing of the pulses to transmit information and perform computation. This realization has stimulated significant research on pulsed neural networks, including theoretical analyses and model development, neurobiological modeling, and hardware implementation. This book presents the complete spectrum of current research in pulsed neural networks and includes the most important work from many of the key scientists in the field. Terrence J. Sejnowski's foreword, "Neural Pulse Coding," presents an overview of the topic. The first half of the book consists of longer tutorial articles spanning neurobiology, theory, algorithms, and hardware. The second half contains a larger number of shorter research chapters that present more advanced concepts. The contributors use consistent notation and terminology throughout the book. Contributors Peter S. Burge, Stephen R. Deiss, Rodney J. Douglas, John G. Elias, Wulfram Gerstner, Alister Hamilton, David Horn, Axel Jahnke, Richard Kempter, Wolfgang Maass, Alessandro Mortara, Alan F. Murray, David P. M. Northmore, Irit Opher, Kostas A. Papathanasiou, Michael Recce, Barry J. P. Rising, Ulrich Roth, Tim Schönauer, Terrence J. Sejnowski, John Shawe-Taylor, Max R. van Daalen, J. Leo van Hemmen, Philippe Venier, Hermann Wagner, Adrian M. Whatley, Anthony M. Zador


Spiking Neuron Models

Spiking Neuron Models

Author: Wulfram Gerstner

Publisher: Cambridge University Press

Published: 2002-08-15

Total Pages: 498

ISBN-13: 9780521890793

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Neurons in the brain communicate by short electrical pulses, the so-called action potentials or spikes. How can we understand the process of spike generation? How can we understand information transmission by neurons? What happens if thousands of neurons are coupled together in a seemingly random network? How does the network connectivity determine the activity patterns? And, vice versa, how does the spike activity influence the connectivity pattern? These questions are addressed in this 2002 introduction to spiking neurons aimed at those taking courses in computational neuroscience, theoretical biology, biophysics, or neural networks. The approach will suit students of physics, mathematics, or computer science; it will also be useful for biologists who are interested in mathematical modelling. The text is enhanced by many worked examples and illustrations. There are no mathematical prerequisites beyond what the audience would meet as undergraduates: more advanced techniques are introduced in an elementary, concrete fashion when needed.


Neuronal Dynamics

Neuronal Dynamics

Author: Wulfram Gerstner

Publisher: Cambridge University Press

Published: 2014-07-24

Total Pages: 591

ISBN-13: 1107060834

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This solid introduction uses the principles of physics and the tools of mathematics to approach fundamental questions of neuroscience.


How to Build a Brain

How to Build a Brain

Author: Chris Eliasmith

Publisher: Oxford University Press

Published: 2013-04-16

Total Pages: 475

ISBN-13: 0199794693

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How to Build a Brain provides a detailed exploration of a new cognitive architecture - the Semantic Pointer Architecture - that takes biological detail seriously, while addressing cognitive phenomena. Topics ranging from semantics and syntax, to neural coding and spike-timing-dependent plasticity are integrated to develop the world's largest functional brain model.


Image Processing Using Pulse-Coupled Neural Networks

Image Processing Using Pulse-Coupled Neural Networks

Author: Thomas Lindblad

Publisher: Springer Science & Business Media

Published: 2005-08-02

Total Pages: 184

ISBN-13: 9783540242185

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* Weitere Angaben Verfasser: Thomas Lindblad is a professor at the Royal Institute of Technology (Physics) in Stockholm. Working and teaching nuclear and environmental physics his main interest is with sensors, signal processing and intelligent data analysis of torrent data from experiments on-line accelerators, in space, etc. Jason Kinser is an associate professor at George Mason University. He has developed a plethora of image processing applications in the medical, military, and industrial fields. He has been responsible for the conversion of PCNN theory into practical applications providing many improvements in both speed and performance


Silicon Implementation of Pulse Coded Neural Networks

Silicon Implementation of Pulse Coded Neural Networks

Author: Mona E. Zaghloul

Publisher: Springer Science & Business Media

Published: 2012-12-06

Total Pages: 293

ISBN-13: 1461526809

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When confronted with the hows and whys of nature's computational engines, some prefer to focus upon neural function: addressing issues of neural system behavior and its relation to natural intelligence. Then there are those who prefer the study of the "mechanics" of neural systems: the nuts and bolts of the "wetware": the neurons and synapses. Those who investigate pulse coded implementations ofartificial neural networks know what it means to stand at the boundary which lies between these two worlds: not just asking why natural neural systems behave as they do, but also how they achieve their marvelous feats. The research results presented in this book not only address more conventional abstract notions of neural-like processing, but also the more specific details ofneural-like processors. It has been established for some time that natural neural systems perform a great deal of information processing via electrochemical pulses. Accordingly, pulse coded neural network concepts are receiving increased attention in artificial neural network research. This increased interest is compounded by continuing advances in the field of VLSI circuit design. This is the first time in history in which it is practical to construct networks of neuron-like circuits of reasonable complexity that can be applied to real problems. We believe that the pioneering work in artificial neural systems presented in this book will lead to further advances that will not only be useful in some practical sense, but may also provide some additional insight into the operation of their natural counterparts.


Plausible Neural Networks for Biological Modelling

Plausible Neural Networks for Biological Modelling

Author: H.A. Mastebroek

Publisher: Springer Science & Business Media

Published: 2001-09-30

Total Pages: 276

ISBN-13: 9780792371922

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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.


Image Processing using Pulse-Coupled Neural Networks

Image Processing using Pulse-Coupled Neural Networks

Author: Thomas Lindblad

Publisher: Springer Science & Business Media

Published: 2013-04-17

Total Pages: 154

ISBN-13: 1447136179

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PCNNs represent a new advance in imaging technology, allowing images to be refined to levels well beyond that of the original. This volume provides an introduction to the topic by reviewing the theoretical foundations as well as a number of image processing applications, including segmentation, edge extraction, texture extraction, object identification, object isolation, motion processing, noise suppression, and image fusion. This is the first book to cover PCNN technology, an area which will have many applications in medical, military and industrial imaging.


Time-Space, Spiking Neural Networks and Brain-Inspired Artificial Intelligence

Time-Space, Spiking Neural Networks and Brain-Inspired Artificial Intelligence

Author: Nikola K. Kasabov

Publisher: Springer

Published: 2018-08-29

Total Pages: 742

ISBN-13: 3662577151

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Spiking neural networks (SNN) are biologically inspired computational models that represent and process information internally as trains of spikes. This monograph book presents the classical theory and applications of SNN, including original author’s contribution to the area. The book introduces for the first time not only deep learning and deep knowledge representation in the human brain and in brain-inspired SNN, but takes that further to develop new types of AI systems, called in the book brain-inspired AI (BI-AI). BI-AI systems are illustrated on: cognitive brain data, including EEG, fMRI and DTI; audio-visual data; brain-computer interfaces; personalized modelling in bio-neuroinformatics; multisensory streaming data modelling in finance, environment and ecology; data compression; neuromorphic hardware implementation. Future directions, such as the integration of multiple modalities, such as quantum-, molecular- and brain information processing, is presented in the last chapter. The book is a research book for postgraduate students, researchers and practitioners across wider areas, including computer and information sciences, engineering, applied mathematics, bio- and neurosciences.


Evolutionary Robotics. From Intelligent Robotics to Artificial Life

Evolutionary Robotics. From Intelligent Robotics to Artificial Life

Author: Takashi Gomi

Publisher: Springer

Published: 2003-06-30

Total Pages: 149

ISBN-13: 3540455027

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This book constitutes the refereed proceedings of the 8th International Symposium on Evolutionary Robotics, ER 2001, held in Tokyo, Japan, in October 2001. The seven revised full papers by the invited speakers Rodney A. Brooks, Dario Floreano, Robert J. Full, Inman Harvey, Owen Holland, Francesco Mondada, and Jordan B. Pollack were carefully selected and revised for presentation in the book. Among the topics addressed are imitation of life and machine consciousness, autonomous vision-based robots, evolved robots, living machines, artificial evolution, bioinspired artificial life locomotion, and mobile robotic systems engineering.