Brain-Inspired Computing


Book Description

This open access book constitutes revised selected papers from the 4th International Workshop on Brain-Inspired Computing, BrainComp 2019, held in Cetraro, Italy, in July 2019. The 11 papers presented in this volume were carefully reviewed and selected for inclusion in this book. They deal with research on brain atlasing, multi-scale models and simulation, HPC and data infra-structures for neuroscience as well as artificial and natural neural architectures.




Memristive Devices for Brain-Inspired Computing


Book Description

Memristive Devices for Brain-Inspired Computing: From Materials, Devices, and Circuits to Applications—Computational Memory, Deep Learning, and Spiking Neural Networks reviews the latest in material and devices engineering for optimizing memristive devices beyond storage applications and toward brain-inspired computing. The book provides readers with an understanding of four key concepts, including materials and device aspects with a view of current materials systems and their remaining barriers, algorithmic aspects comprising basic concepts of neuroscience as well as various computing concepts, the circuits and architectures implementing those algorithms based on memristive technologies, and target applications, including brain-inspired computing, computational memory, and deep learning. This comprehensive book is suitable for an interdisciplinary audience, including materials scientists, physicists, electrical engineers, and computer scientists. - Provides readers an overview of four key concepts in this emerging research topic including materials and device aspects, algorithmic aspects, circuits and architectures and target applications - Covers a broad range of applications, including brain-inspired computing, computational memory, deep learning and spiking neural networks - Includes perspectives from a wide range of disciplines, including materials science, electrical engineering and computing, providing a unique interdisciplinary look at the field




Neuromorphic Devices for Brain-inspired Computing


Book Description

Explore the cutting-edge of neuromorphic technologies with applications in Artificial Intelligence In Neuromorphic Devices for Brain-Inspired Computing: Artificial Intelligence, Perception, and Robotics, a team of expert engineers delivers a comprehensive discussion of all aspects of neuromorphic electronics designed to assist researchers and professionals to understand and apply all manner of brain-inspired computing and perception technologies. The book covers both memristic and neuromorphic devices, including spintronic, multi-terminal, and neuromorphic perceptual applications. Summarizing recent progress made in five distinct configurations of brain-inspired computing, the authors explore this promising technology’s potential applications in two specific areas: neuromorphic computing systems and neuromorphic perceptual systems. The book also includes: A thorough introduction to two-terminal neuromorphic memristors, including memristive devices and resistive switching mechanisms Comprehensive explorations of spintronic neuromorphic devices and multi-terminal neuromorphic devices with cognitive behaviors Practical discussions of neuromorphic devices based on chalcogenide and organic materials In-depth examinations of neuromorphic computing and perceptual systems with emerging devices Perfect for materials scientists, biochemists, and electronics engineers, Neuromorphic Devices for Brain-Inspired Computing: Artificial Intelligence, Perception, and Robotics will also earn a place in the libraries of neurochemists, neurobiologists, and neurophysiologists.




Brain-mind Machinery


Book Description

Brain and mind continue to be a topic of enormous scientific interest. With the recent advances in measuring instruments such as two-photon laser scanning microscopy and fMRI, the neuronal connectivity and circuitry of how the brain's various regions are hierarchically interconnected and organized are better understood now than ever before. By reverse engineering the brain, computer scientists hope to build cognitively intelligent systems that will revolutionize the artificial intelligence paradigm. Brain-Mind Machinery provides a walkthrough to the world of brain-inspired computing and mind-related questions. Bringing together diverse viewpoints and expertise from multidisciplinary communities, the book explores the human quest to build a thinking machine with human-like capabilities. Readers will acquire a first-hand understanding of the brain and mind mechanisms and machineries, as well as how much we have progressed in and how far we are from building a truly general intelligent system like the human brain.




Brain-Inspired Information Technology


Book Description

"Brain-inspired information technology" is one of key concepts for the development of information technology in the next generation. Explosive progress of computer technology has been continuing based on a simple principle called "if-then rule". This means that the programmer of software have to direct every action of the computer programs in response to various inputs. There inherently is a limitation of complexity because we human have a limited capacity for managing complex systems. Actually, many bugs, mistakes of programming, exist in computer software, and it is quite difficult to extinguish them. The parts of computer programs where computer viruses attack are also a kind of programming mistakes, called security hole. Of course, human body or nervous system is not perfect. No creator or director, however, exists for us. The function of our brain is equipped by learning, self-organization, natural selection, and etc, resulting in adaptive and flexible information system. Brain-inspired information technology is aiming to realize such nature-made information processing system by using present computer system or specific hardware. To do so, researchers in various research fields are getting together to inspire each other and challenge cooperatively for the same goal.




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


Book Description

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.




Artificial Intelligence in the Age of Neural Networks and Brain Computing


Book Description

Artificial Intelligence in the Age of Neural Networks and Brain Computing, Second Edition demonstrates that present disruptive implications and applications of AI is a development of the unique attributes of neural networks, mainly machine learning, distributed architectures, massive parallel processing, black-box inference, intrinsic nonlinearity, and smart autonomous search engines. The book covers the major basic ideas of "brain-like computing" behind AI, provides a framework to deep learning, and launches novel and intriguing paradigms as possible future alternatives. The present success of AI-based commercial products proposed by top industry leaders, such as Google, IBM, Microsoft, Intel, and Amazon, can be interpreted using the perspective presented in this book by viewing the co-existence of a successful synergism among what is referred to as computational intelligence, natural intelligence, brain computing, and neural engineering. The new edition has been updated to include major new advances in the field, including many new chapters. - Developed from the 30th anniversary of the International Neural Network Society (INNS) and the 2017 International Joint Conference on Neural Networks (IJCNN - Authored by top experts, global field pioneers, and researchers working on cutting-edge applications in signal processing, speech recognition, games, adaptive control and decision-making - Edited by high-level academics and researchers in intelligent systems and neural networks - Includes all new chapters, including topics such as Frontiers in Recurrent Neural Network Research; Big Science, Team Science, Open Science for Neuroscience; A Model-Based Approach for Bridging Scales of Cortical Activity; A Cognitive Architecture for Object Recognition in Video; How Brain Architecture Leads to Abstract Thought; Deep Learning-Based Speech Separation and Advances in AI, Neural Networks




Bio-inspired Neurocomputing


Book Description

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.




Nature-Inspired Computing and Optimization


Book Description

The book provides readers with a snapshot of the state of the art in the field of nature-inspired computing and its application in optimization. The approach is mainly practice-oriented: each bio-inspired technique or algorithm is introduced together with one of its possible applications. Applications cover a wide range of real-world optimization problems: from feature selection and image enhancement to scheduling and dynamic resource management, from wireless sensor networks and wiring network diagnosis to sports training planning and gene expression, from topology control and morphological filters to nutritional meal design and antenna array design. There are a few theoretical chapters comparing different existing techniques, exploring the advantages of nature-inspired computing over other methods, and investigating the mixing time of genetic algorithms. The book also introduces a wide range of algorithms, including the ant colony optimization, the bat algorithm, genetic algorithms, the collision-based optimization algorithm, the flower pollination algorithm, multi-agent systems and particle swarm optimization. This timely book is intended as a practice-oriented reference guide for students, researchers and professionals.




Future Trends of HPC in a Disruptive Scenario


Book Description

The realization that the use of components off the shelf (COTS) could reduce costs sparked the evolution of the massive parallel computing systems available today. The main problem with such systems is the development of suitable operating systems, algorithms and application software that can utilise the potential processing power of large numbers of processors. As a result, systems comprising millions of processors are still limited in the applications they can efficiently solve. Two alternative paradigms that may offer a solution to this problem are Quantum Computers (QC) and Brain Inspired Computers (BIC). This book presents papers from the 14th edition of the biennial international conference on High Performance Computing - From Clouds and Big Data to Exascale and Beyond, held in Cetraro, Italy, from 2 - 6 July 2018. It is divided into 4 sections covering data science, quantum computing, high-performance computing, and applications. The papers presented during the workshop covered a wide spectrum of topics on new developments in the rapidly evolving supercomputing field – including QC and BIC – and a selection of contributions presented at the workshop are included in this volume. In addition, two papers presented at a workshop on Brain Inspired Computing in 2017 and an overview of work related to data science executed by a number of universities in the USA, parts of which were presented at the 2018 and previous workshops, are also included. The book will be of interest to all those whose work involves high-performance computing.