Download or read book Neuro inspired Information Processing written by Alain Cappy and published by John Wiley & Sons. This book was released on 2020-06-16 with total page 240 pages. Available in PDF, EPUB and Kindle. Book excerpt: With the end of Moore's law and the emergence of new application needs such as those of the Internet of Things (IoT) or artificial intelligence (AI), neuro-inspired, or neuromorphic, information processing is attracting more and more attention from the scientific community. Its principle is to emulate in a simplified way the formidable machine to process information which is the brain, with neurons and artificial synapses organized in network. These networks can be software – and therefore implemented in the form of a computer program – but also hardware and produced by nanoelectronic circuits. The material path allows very low energy consumption, and the possibility of faithfully reproducing the shape and dynamics of the action potentials of living neurons (biomimetic approach) or even being up to a thousand times faster (high frequency approach). This path is promising and welcomed by the major manufacturers of nanoelectronics, as circuits can now today integrate several million neurons and artificial synapses.
Download or read book Neuro inspired Information Processing written by Alain Cappy and published by John Wiley & Sons. This book was released on 2020-03-31 with total page 240 pages. Available in PDF, EPUB and Kindle. Book excerpt: With the end of Moore's law and the emergence of new application needs such as those of the Internet of Things (IoT) or artificial intelligence (AI), neuro-inspired, or neuromorphic, information processing is attracting more and more attention from the scientific community. Its principle is to emulate in a simplified way the formidable machine to process information which is the brain, with neurons and artificial synapses organized in network. These networks can be software – and therefore implemented in the form of a computer program – but also hardware and produced by nanoelectronic circuits. The 'material' path allows very low energy consumption, and the possibility of faithfully reproducing the shape and dynamics of the action potentials of living neurons (biomimetic approach) or even being up to a thousand times faster (high frequency approach). This path is promising and welcomed by the major manufacturers of nanoelectronics, as circuits can now today integrate several million neurons and artificial synapses.
Download or read book Atomic Switch written by Masakazu Aono and published by Springer Nature. This book was released on 2020-03-02 with total page 270 pages. Available in PDF, EPUB and Kindle. Book excerpt: Written by the inventors and leading experts of this new field, the book results from the International Symposium on “Atomic Switch: Invention, Practical use and Future Prospects” which took place in Tsukuba, Japan on March 27th - 28th, 2017. The book chapters cover the different trends from the science and technology of atomic switches to their applications like brain-type information processing, artificial intelligence (AI) and completely novel functional electronic nanodevices. The current practical uses of the atomic switch are also described. As compared with the conventional semiconductor transistor switch, the atomic switch is more compact (~1/10) with much lower power consumption (~1/10) and scarcely influenced by strong electromagnetic noise and radiation including cosmic rays in space (~1/100). As such, this book is of interest to researchers, scholars and students willing to explore new materials, to refine the nanofabrication methods and to explore new and efficient device architectures.
Download or read book Time Space Spiking Neural Networks and Brain Inspired Artificial Intelligence written by Nikola K. Kasabov and published by Springer. This book was released on 2018-08-29 with total page 742 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Bio inspired Neurocomputing written by Akash Kumar Bhoi and published by Springer Nature. This book was released on 2020-07-21 with total page 427 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book covers the latest technological advances in neuro-computational intelligence in biological processes where the primary focus is on biologically inspired neuro-computational techniques. The theoretical and practical aspects of biomedical neural computing, brain-inspired computing, bio-computational models, artificial intelligence (AI) and machine learning (ML) approaches in biomedical data analytics are covered along with their qualitative and quantitative features. The contents cover numerous computational applications, methodologies and emerging challenges in the field of bio-soft computing and bio-signal processing. The authors have taken meticulous care in describing the fundamental concepts, identifying the research gap and highlighting the problems with the strategical computational approaches to address the ongoing challenges in bio-inspired models and algorithms. Given the range of topics covered, this book can be a valuable resource for students, researchers as well as practitioners interested in the rapidly evolving field of neurocomputing and biomedical data analytics.
Download or read book Neural Information Processing written by Masumi Ishikawa and published by Springer Science & Business Media. This book was released on 2008-06-16 with total page 1165 pages. Available in PDF, EPUB and Kindle. Book excerpt: The two volume set LNCS 4984 and LNCS 4985 constitutes the thoroughly refereed post-conference proceedings of the 14th International Conference on Neural Information Processing, ICONIP 2007, held in Kitakyushu, Japan, in November 2007, jointly with BRAINIT 2007, the 4th International Conference on Brain-Inspired Information Technology. The 228 revised full papers presented were carefully reviewed and selected from numerous ordinary paper submissions and 15 special organized sessions. The 116 papers of the first volume are organized in topical sections on computational neuroscience, learning and memory, neural network models, supervised/unsupervised/reinforcement learning, statistical learning algorithms, optimization algorithms, novel algorithms, as well as motor control and vision. The second volume contains 112 contributions related to statistical and pattern recognition algorithms, neuromorphic hardware and implementations, robotics, data mining and knowledge discovery, real world applications, cognitive and hybrid intelligent systems, bioinformatics, neuroinformatics, brain-conputer interfaces, and novel approaches.
Download or read book Neuro inspired Architectures for the Acquisition and Processing of Visual Information written by Ala Aboudib and published by . This book was released on 2016 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Computer vision and machine learning are two hot research topics that have witnessed major breakthroughs in recent years. Much of the advances in these domains have been the fruits of many years of research on the visual cortex and brain function. In this thesis, we focus on designing neuro-inspired architectures for processing information along three different stages of the visual cortex. At the lowest stage, we propose a neural model for the acquisition of visual signals. This model is adapted to emulating eye movements and is closely inspired by the function and the architecture of the retina and early layers of the ventral stream. On the highest stage, we address the memory problem. We focus on an existing neuro-inspired associative memory model called the Sparse Clustered Network. We propose a new information retrieval algorithm that offers more flexibility and a better performance over existing ones. Furthermore, we suggest a generic formulation within which all existing retrieval algorithms can fit. It can also be used to guide the design of new retrieval approaches in a modular fashion. On the intermediate stage, we propose a new way for dealing with the image feature correspondence problem using a neural network model. This model deploys the structure of Sparse Clustered Networks, and offers a gain in matching performance over state-of-the-art, and provides a useful insight on how neuro-inspired architectures can serve as a substrate for implementing various vision tasks.
Download or read book Neuroinformatics written by Fouad Sabry and published by One Billion Knowledgeable. This book was released on 2022-08-04 with total page 404 pages. Available in PDF, EPUB and Kindle. Book excerpt: What Is Neuroinformatics The fields of informatics and neurology have been combined to establish the discipline of neuroinformatics. The processing of data and information in the field of neuroscience using artificial neural networks is referred to as neuroinformatics. There are three primary areas in which neuroinformatics needs to be utilized, and they are as follows: the creation of computer models of the nervous system and the processes that take place in the brain.the creation of tools for analyzing and modeling data from the field of neuroscience, the creation of tools and databases for the management and sharing of data from the field of neuroscience at all levels of analysis, How You Will Benefit (I) Insights, and validations about the following topics: Chapter 1: Neuroinformatics Chapter 2: Neuroscience Chapter 3: Mind uploading Chapter 4: Computational neuroscience Chapter 5: Bio-inspired computing Chapter 6: Neuromorphic engineering Chapter 7: Terry Sejnowski Chapter 8: Neural network Chapter 9: Krasnow Institute for Advanced Study Chapter 10: Neural computation Chapter 11: Blue Brain Project Chapter 12: International Neuroinformatics Coordinating Facility Chapter 13: Human Brain Project Chapter 14: Multi-simulation coordinator Chapter 15: Brain simulation Chapter 16: Informatics Chapter 17: Nervous system network models Chapter 18: Outline of brain mapping Chapter 19: Upinder Singh Bhalla Chapter 20: Predictive coding Chapter 21: MIT Department of Brain and Cognitive Sciences (II) Answering the public top questions about neuroinformatics. (III) Real world examples for the usage of neuroinformatics in many fields. (IV) 17 appendices to explain, briefly, 266 emerging technologies in each industry to have 360-degree full understanding of neuroinformatics' technologies. Who This Book Is For Professionals, undergraduate and graduate students, enthusiasts, hobbyists, and those who want to go beyond basic knowledge or information for any kind of neuroinformatics.
Download or read book Advances in Neuro Information Processing written by Mario Köppen and published by Springer. This book was released on 2009-07-30 with total page 1273 pages. Available in PDF, EPUB and Kindle. Book excerpt: The two volume set LNCS 5506 and LNCS 5507 constitutes the thoroughly refereed post-conference proceedings of the 15th International Conference on Neural Information Processing, ICONIP 2008, held in Auckland, New Zealand, in November 2008. The 260 revised full papers presented were carefully reviewed and selected from numerous ordinary paper submissions and 15 special organized sessions. 116 papers are published in the first volume and 112 in the second volume. The contributions deal with topics in the areas of data mining methods for cybersecurity, computational models and their applications to machine learning and pattern recognition, lifelong incremental learning for intelligent systems, application of intelligent methods in ecological informatics, pattern recognition from real-world information by svm and other sophisticated techniques, dynamics of neural networks, recent advances in brain-inspired technologies for robotics, neural information processing in cooperative multi-robot systems.
Download or read book An Introduction to Neural Information Processing written by Peiji Liang and published by Springer. This book was released on 2015-12-22 with total page 338 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides an overview of neural information processing research, which is one of the most important branches of neuroscience today. Neural information processing is an interdisciplinary subject, and the merging interaction between neuroscience and mathematics, physics, as well as information science plays a key role in the development of this field. This book begins with the anatomy of the central nervous system, followed by an introduction to various information processing models at different levels. The authors all have extensive experience in mathematics, physics and biomedical engineering, and have worked in this multidisciplinary area for a number of years. They present classical examples of how the pioneers in this field used theoretical analysis, mathematical modeling and computer simulation to solve neurobiological problems, and share their experiences and lessons learned. The book is intended for researchers and students with a mathematics, physics or informatics background who are interested in brain research and keen to understand the necessary neurobiology and how they can use their specialties to address neurobiological problems. It is also provides inspiration for neuroscience students who are interested in learning how to use mathematics, physics or informatics approaches to solve problems in their field.
Download or read book Artificial Neural Networks as Models of Neural Information Processing written by Marcel van Gerven and published by Frontiers Media SA. This book was released on 2018-02-01 with total page 220 pages. Available in PDF, EPUB and Kindle. Book excerpt: Modern neural networks gave rise to major breakthroughs in several research areas. In neuroscience, we are witnessing a reappraisal of neural network theory and its relevance for understanding information processing in biological systems. The research presented in this book provides various perspectives on the use of artificial neural networks as models of neural information processing. We consider the biological plausibility of neural networks, performance improvements, spiking neural networks and the use of neural networks for understanding brain function.
Download or read book Neural Information Processing written by Akira Hirose and published by Springer. This book was released on 2016-09-30 with total page 750 pages. Available in PDF, EPUB and Kindle. Book excerpt: The four volume set LNCS 9947, LNCS 9948, LNCS 9949, and LNCS 9950 constitues the proceedings of the 23rd International Conference on Neural Information Processing, ICONIP 2016, held in Kyoto, Japan, in October 2016. The 296 full papers presented were carefully reviewed and selected from 431 submissions. The 4 volumes are organized in topical sections on deep and reinforcement learning; big data analysis; neural data analysis; robotics and control; bio-inspired/energy efficient information processing; whole brain architecture; neurodynamics; bioinformatics; biomedical engineering; data mining and cybersecurity workshop; machine learning; neuromorphic hardware; sensory perception; pattern recognition; social networks; brain-machine interface; computer vision; time series analysis; data-driven approach for extracting latent features; topological and graph based clustering methods; computational intelligence; data mining; deep neural networks; computational and cognitive neurosciences; theory and algorithms.
Download or read book Towards a Brain inspired Information Processing System written by Karim El-Laithy and published by LAP Lambert Academic Publishing. This book was released on 2012-02 with total page 240 pages. Available in PDF, EPUB and Kindle. Book excerpt: Biological neural systems in general and the central nervous system specifically exhibit a strikingly efficient computational power along with an extreme flexible and adaptive basis for acquiring and integrating new knowledge. Acquiring more insights into the actual mechanisms of information processing within the brain and their computational capabilities is a core objective of modern computer science, computational sciences and neuroscience. There is however a significant lack of knowledge regarding the basic information processing within the brain. In order to have more insights into these basic information processing methods, this book presents an approach that investigates the underlying mechanisms allowing the brain to be capable of performing such massive amounts of computational tasks with a sustainable efficiency and flexibility. A main focus of this work is the role of synapses and their involved dynamics in the brain's computational power. This work investigates, models and analyses the synaptic dynamics with integration into the level of dynamic neural networks.
Download or read book Advances in Neuro Information Processing written by Mario Köppen and published by Springer. This book was released on 2009-07-30 with total page 1108 pages. Available in PDF, EPUB and Kindle. Book excerpt: The two volume set LNCS 5506 and LNCS 5507 constitutes the thoroughly refereed post-conference proceedings of the 15th International Conference on Neural Information Processing, ICONIP 2008, held in Auckland, New Zealand, in November 2008. The 260 revised full papers presented were carefully reviewed and selected from numerous ordinary paper submissions and 15 special organized sessions. 116 papers are published in the first volume and 112 in the second volume. The contributions deal with topics in the areas of data mining methods for cybersecurity, computational models and their applications to machine learning and pattern recognition, lifelong incremental learning for intelligent systems, application of intelligent methods in ecological informatics, pattern recognition from real-world information by svm and other sophisticated techniques, dynamics of neural networks, recent advances in brain-inspired technologies for robotics, neural information processing in cooperative multi-robot systems.
Download or read book Synergetic Phenomena in Active Lattices written by Vladimir I. Nekorkin and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 371 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this book, the authors deal with basic concepts and models, with methodologies for studying the existence and stability of motions, understanding the mechanisms of formation of patterns and waves, their propagation and interactions in active lattice systems, and about how much cooperation or competition between order and chaos is crucial for synergetic behavior and evolution.
Download or read book Neuromorphic Photonics written by Paul R. Prucnal and published by CRC Press. This book was released on 2017-05-08 with total page 295 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book sets out to build bridges between the domains of photonic device physics and neural networks, providing a comprehensive overview of the emerging field of "neuromorphic photonics." It includes a thorough discussion of evolution of neuromorphic photonics from the advent of fiber-optic neurons to today’s state-of-the-art integrated laser neurons, which are a current focus of international research. Neuromorphic Photonics explores candidate interconnection architectures and devices for integrated neuromorphic networks, along with key functionality such as learning. It is written at a level accessible to graduate students, while also intending to serve as a comprehensive reference for experts in the field.
Download or read book Photonic Reservoir Computing written by Daniel Brunner and published by Walter de Gruyter GmbH & Co KG. This book was released on 2019-07-08 with total page 391 pages. Available in PDF, EPUB and Kindle. Book excerpt: Photonics has long been considered an attractive substrate for next generation implementations of machine-learning concepts. Reservoir Computing tremendously facilitated the realization of recurrent neural networks in analogue hardware. This concept exploits the properties of complex nonlinear dynamical systems, giving rise to photonic reservoirs implemented by semiconductor lasers, telecommunication modulators and integrated photonic chips.
