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Author : Shuangming Yang
Publisher : Springer Nature
ISBN 13 : 3031578732
Total Pages : 256 pages
Book Rating : 4.0/5 (315 download)
Download or read book Neuromorphic Intelligence written by Shuangming Yang and published by Springer Nature. This book was released on with total page 256 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Qing Wan
Publisher : John Wiley & Sons
ISBN 13 : 3527349790
Total Pages : 258 pages
Book Rating : 4.5/5 (273 download)
Download or read book Neuromorphic Devices for Brain-inspired Computing written by Qing Wan and published by John Wiley & Sons. This book was released on 2022-05-16 with total page 258 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Author : Jordi Suñé
Publisher : MDPI
ISBN 13 : 3039285769
Total Pages : 244 pages
Book Rating : 4.0/5 (392 download)
Download or read book Memristors for Neuromorphic Circuits and Artificial Intelligence Applications written by Jordi Suñé and published by MDPI. This book was released on 2020-04-09 with total page 244 pages. Available in PDF, EPUB and Kindle. Book excerpt: Artificial Intelligence (AI) has found many applications in the past decade due to the ever increasing computing power. Artificial Neural Networks are inspired in the brain structure and consist in the interconnection of artificial neurons through artificial synapses. Training these systems requires huge amounts of data and, after the network is trained, it can recognize unforeseen data and provide useful information. The so-called Spiking Neural Networks behave similarly to how the brain functions and are very energy efficient. Up to this moment, both spiking and conventional neural networks have been implemented in software programs running on conventional computing units. However, this approach requires high computing power, a large physical space and is energy inefficient. Thus, there is an increasing interest in developing AI tools directly implemented in hardware. The first hardware demonstrations have been based on CMOS circuits for neurons and specific communication protocols for synapses. However, to further increase training speed and energy efficiency while decreasing system size, the combination of CMOS neurons with memristor synapses is being explored. The memristor is a resistor with memory which behaves similarly to biological synapses. This book explores the state-of-the-art of neuromorphic circuits implementing neural networks with memristors for AI applications.
Author : Hong Qu
Publisher : Elsevier
ISBN 13 : 0443328218
Total Pages : 222 pages
Book Rating : 4.4/5 (433 download)
Download or read book Towards Neuromorphic Machine Intelligence written by Hong Qu and published by Elsevier. This book was released on 2024-06-28 with total page 222 pages. Available in PDF, EPUB and Kindle. Book excerpt: Towards Neuromorphic Machine Intelligence: Spike-Based Representation, Learning and Applications provides readers with in-depth understanding of Spiking Neural Networks (SNN), which is a burgeoning research branch of Artificial Neural Networks (ANN), AI, and Machine Learning that sits at the heart of the integration between Computer Science and Neural Engineering. In recent years, neural networks have re-emerged in relation to AI, representing a well-grounded paradigm rooted in disciplines from physics and psychology to information science and engineering. This book represents one of the established cross-over areas where neurophysiology, cognition, and neural engineering coincide with the development of new Machine Learning and AI paradigms. There are many excellent theoretical achievements in neuron models, learning algorithms, network architecture and so on. But these achievements are numerous and scattered, with a lack of straightforward systematic integration, making it difficult for researchers to assimilate and apply. As the third generation of Artificial Neural Networks (ANN), Spiking Neural Networks (SNN) simulate the neuron dynamics and information transmission in a biological neural system in more detail, which is a cross-product of computer science and neuroscience. The primary target audience of this book is divided into two categories: artificial intelligence researchers who know nothing about SNN, and researchers who know a lot about SNN. The former needs to acquire fundamental knowledge of SNN, but the challenge is that a large number of existing literatures on SNN only slightly mention the basic knowledge of SNN, or are too superficial, and this book gives a systematic explanation from scratch. The latter needs to learn about some novel research achievements in the field of SNN, and this book introduces the latest research results on different aspects of SNN and provides detailed simulation processes to facilitate readers' replication. In addition, the book introduces neuromorphic hardware architecture as a further extension of the SNN system. The book starts with the birth and development of SNN, and then introduces the main research hotspots, including spiking neuron models, learning algorithms, network architectures, and neuromorphic hardware. Therefore, the book provides readers with easy access to both the foundational concepts and recent research findings in SNN. Introduces Spiking Neural Networks (SNN), a new generation of biologically inspired artificial intelligence Systematically presents basic concepts of SNN, neuron and network models, learning algorithms, and neuromorphic hardware Introduces the latest research results on various aspects of SNN and provides detailed simulation processes to facilitate readers' replication
Author : Qiang Yu
Publisher : Springer
ISBN 13 : 3319553100
Total Pages : 180 pages
Book Rating : 4.3/5 (195 download)
Download or read book Neuromorphic Cognitive Systems written by Qiang Yu and published by Springer. This book was released on 2017-05-03 with total page 180 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents neuromorphic cognitive systems from a learning and memory-centered perspective. It illustrates how to build a system network of neurons to perform spike-based information processing, computing, and high-level cognitive tasks. It is beneficial to a wide spectrum of readers, including undergraduate and postgraduate students and researchers who are interested in neuromorphic computing and neuromorphic engineering, as well as engineers and professionals in industry who are involved in the design and applications of neuromorphic cognitive systems, neuromorphic sensors and processors, and cognitive robotics. The book formulates a systematic framework, from the basic mathematical and computational methods in spike-based neural encoding, learning in both single and multi-layered networks, to a near cognitive level composed of memory and cognition. Since the mechanisms for integrating spiking neurons integrate to formulate cognitive functions as in the brain are little understood, studies of neuromorphic cognitive systems are urgently needed. The topics covered in this book range from the neuronal level to the system level. In the neuronal level, synaptic adaptation plays an important role in learning patterns. In order to perform higher-level cognitive functions such as recognition and memory, spiking neurons with learning abilities are consistently integrated, building a system with encoding, learning and memory functionalities. The book describes these aspects in detail.
Author : Nikola K. Kasabov
Publisher : Springer
ISBN 13 : 3662577151
Total Pages : 742 pages
Book Rating : 4.6/5 (625 download)
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.
Author : Jeffrey L. Krichmar
Publisher : Cambridge University Press
ISBN 13 : 1139498576
Total Pages : pages
Book Rating : 4.1/5 (394 download)
Download or read book Neuromorphic and Brain-Based Robots written by Jeffrey L. Krichmar and published by Cambridge University Press. This book was released on 2011-09-01 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Neuromorphic and brain-based robotics have enormous potential for furthering our understanding of the brain. By embodying models of the brain on robotic platforms, researchers can investigate the roots of biological intelligence and work towards the development of truly intelligent machines. This book provides a broad introduction to this groundbreaking area for researchers from a wide range of fields, from engineering to neuroscience. Case studies explore how robots are being used in current research, including a whisker system that allows a robot to sense its environment and neurally inspired navigation systems that show impressive mapping results. Looking to the future, several chapters consider the development of cognitive, or even conscious robots that display the adaptability and intelligence of biological organisms. Finally, the ethical implications of intelligent robots are explored, from morality and Asimov's three laws to the question of whether robots have rights.
Author : Hisao Ishibuchi
Publisher : EOLSS Publications
ISBN 13 : 1780210213
Total Pages : 410 pages
Book Rating : 4.7/5 (82 download)
Download or read book Computational Intelligence - Volume II written by Hisao Ishibuchi and published by EOLSS Publications. This book was released on 2015-12-30 with total page 410 pages. Available in PDF, EPUB and Kindle. Book excerpt: Computational intelligence is a component of Encyclopedia of Technology, Information, and Systems Management Resources in the global Encyclopedia of Life Support Systems (EOLSS), which is an integrated compendium of twenty one Encyclopedias. Computational intelligence is a rapidly growing research field including a wide variety of problem-solving techniques inspired by nature. Traditionally computational intelligence consists of three major research areas: Neural Networks, Fuzzy Systems, and Evolutionary Computation. Neural networks are mathematical models inspired by brains. Neural networks have massively parallel network structures with many neurons and weighted connections. Whereas each neuron has a simple input-output relation, a neural network with many neurons can realize a highly non-linear complicated mapping. Connection weights between neurons can be adjusted in an automated manner by a learning algorithm to realize a non-linear mapping required in a particular application task. Fuzzy systems are mathematical models proposed to handle inherent fuzziness in natural language. For example, it is very difficult to mathematically define the meaning of “cold” in everyday conversations such as “It is cold today” and “Can I have cold water”. The meaning of “cold” may be different in a different situation. Even in the same situation, a different person may have a different meaning. Fuzzy systems offer a mathematical mechanism to handle inherent fuzziness in natural language. As a result, fuzzy systems have been successfully applied to real-world problems by extracting linguistic knowledge from human experts in the form of fuzzy IF-THEN rules. Evolutionary computation includes various population-based search algorithms inspired by evolution in nature. Those algorithms usually have the following three mechanisms: fitness evaluation to measure the quality of each solution, selection to choose good solutions from the current population, and variation operators to generate offspring from parents. Evolutionary computation has high applicability to a wide range of optimization problems with different characteristics since it does not need any explicit mathematical formulations of objective functions. For example, simulation-based fitness evaluation is often used in evolutionary design. Subjective fitness evaluation by a human user is also often used in evolutionary art and music. These volumes are aimed at the following five major target audiences: University and College students Educators, Professional practitioners, Research personnel and Policy analysts, managers, and decision makers.
Author : Balwinder Raj
Publisher : John Wiley & Sons
ISBN 13 : 1394204353
Total Pages : 388 pages
Book Rating : 4.3/5 (942 download)
Download or read book Integrated Devices for Artificial Intelligence and VLSI written by Balwinder Raj and published by John Wiley & Sons. This book was released on 2024-09-04 with total page 388 pages. Available in PDF, EPUB and Kindle. Book excerpt: With its in-depth exploration of the close connection between microelectronics, AI, and VLSI technology, this book offers valuable insights into the cutting-edge techniques and tools used in VLSI design automation, making it an essential resource for anyone seeking to stay ahead in the rapidly evolving field of VLSI design. Very large-scale integration (VLSI) is the inter-disciplinary science of utilizing advanced semiconductor technology to create various functions of computer system. This book addresses the close link of microelectronics and artificial intelligence (AI). By combining VLSI technology, a very powerful computer architecture confinement is possible. To overcome problems at different design stages, researchers introduced artificial intelligent (AI) techniques in VLSI design automation. AI techniques, such as knowledge-based and expert systems, first try to define the problem and then choose the best solution from the domain of possible solutions. These days, several CAD technologies, such as Synopsys and Mentor Graphics, are specifically created to increase the automation of VLSI design. When a task is completed using the appropriate tool, each stage of the task design produces outcomes that are more productive than typical. However, combining all of these tools into a single package offer has drawbacks. We can’t really use every outlook without sacrificing the efficiency and usefulness of our output. The researchers decided to include AI approaches into VLSI design automation in order to get around these obstacles. AI is one of the fastest growing tools in the world of technology and innovation that helps to make computers more reliable and easy to use. Artificial Intelligence in VLSI design has provided high-end and more feasible solutions to the difficulties faced by the VLSI industry. Physical design, RTL design, STA, etc. are some of the most in-demand courses to enter the VLSI industry. These courses help develop a better understanding of the many tools like Synopsis. With each new dawn, artificial intelligence in VLSI design is continually evolving, and new opportunities are being investigated.
Author : Dr R. Keerthika
Publisher : Inkbound Publishers
ISBN 13 : 8196822340
Total Pages : 224 pages
Book Rating : 4.1/5 (968 download)
Download or read book Algorithms of Intelligence: Exploring the World of Machine Learning written by Dr R. Keerthika and published by Inkbound Publishers. This book was released on 2022-01-20 with total page 224 pages. Available in PDF, EPUB and Kindle. Book excerpt: Delve into the fascinating world of machine learning with this comprehensive guide, which unpacks the algorithms driving today's intelligent systems. From foundational concepts to advanced applications, this book is essential for anyone looking to understand the mechanics behind AI.
Author : Alex Meystel
Publisher :
ISBN 13 :
Total Pages : 688 pages
Book Rating : 4.3/5 (91 download)
Download or read book Measuring the Performance and Intelligence of Systems written by Alex Meystel and published by . This book was released on 2001 with total page 688 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : André van Schaik
Publisher : Frontiers Media SA
ISBN 13 : 288919454X
Total Pages : 183 pages
Book Rating : 4.8/5 (891 download)
Download or read book Neuromorphic Engineering Systems and Applications written by André van Schaik and published by Frontiers Media SA. This book was released on 2015-07-05 with total page 183 pages. Available in PDF, EPUB and Kindle. Book excerpt: Neuromorphic engineering has just reached its 25th year as a discipline. In the first two decades neuromorphic engineers focused on building models of sensors, such as silicon cochleas and retinas, and building blocks such as silicon neurons and synapses. These designs have honed our skills in implementing sensors and neural networks in VLSI using analog and mixed mode circuits. Over the last decade the address event representation has been used to interface devices and computers from different designers and even different groups. This facility has been essential for our ability to combine sensors, neural networks, and actuators into neuromorphic systems. More recently, several big projects have emerged to build very large scale neuromorphic systems. The Telluride Neuromorphic Engineering Workshop (since 1994) and the CapoCaccia Cognitive Neuromorphic Engineering Workshop (since 2009) have been instrumental not only in creating a strongly connected research community, but also in introducing different groups to each other’s hardware. Many neuromorphic systems are first created at one of these workshops. With this special research topic, we showcase the state-of-the-art in neuromorphic systems.
Author :
Publisher : BoD – Books on Demand
ISBN 13 : 1803561432
Total Pages : 298 pages
Book Rating : 4.8/5 (35 download)
Download or read book Neuromorphic Computing written by and published by BoD – Books on Demand. This book was released on 2023-11-15 with total page 298 pages. Available in PDF, EPUB and Kindle. Book excerpt: Dive into the cutting-edge world of Neuromorphic Computing, a groundbreaking volume that unravels the secrets of brain-inspired computational paradigms. Spanning neuroscience, artificial intelligence, and hardware design, this book presents a comprehensive exploration of neuromorphic systems, empowering both experts and newcomers to embrace the limitless potential of brain-inspired computing. Discover the fundamental principles that underpin neural computation as we journey through the origins of neuromorphic architectures, meticulously crafted to mimic the brain’s intricate neural networks. Unlock the true essence of learning mechanisms – unsupervised, supervised, and reinforcement learning – and witness how these innovations are shaping the future of artificial intelligence.
Author : Christos Volos
Publisher : Academic Press
ISBN 13 : 0128232021
Total Pages : 570 pages
Book Rating : 4.1/5 (282 download)
Download or read book Mem-elements for Neuromorphic Circuits with Artificial Intelligence Applications written by Christos Volos and published by Academic Press. This book was released on 2021-06-17 with total page 570 pages. Available in PDF, EPUB and Kindle. Book excerpt: Mem-elements for Neuromorphic Circuits with Artificial Intelligence Applications illustrates recent advances in the field of mem-elements (memristor, memcapacitor, meminductor) and their applications in nonlinear dynamical systems, computer science, analog and digital systems, and in neuromorphic circuits and artificial intelligence. The book is mainly devoted to recent results, critical aspects and perspectives of ongoing research on relevant topics, all involving networks of mem-elements devices in diverse applications. Sections contribute to the discussion of memristive materials and transport mechanisms, presenting various types of physical structures that can be fabricated to realize mem-elements in integrated circuits and device modeling. As the last decade has seen an increasing interest in recent advances in mem-elements and their applications in neuromorphic circuits and artificial intelligence, this book will attract researchers in various fields. Covers a broad range of interdisciplinary topics between mathematics, circuits, realizations, and practical applications related to nonlinear dynamical systems, nanotechnology, analog and digital systems, computer science and artificial intelligence Presents recent advances in the field of mem-elements (memristor, memcapacitor, meminductor) Includes interesting applications of mem-elements in nonlinear dynamical systems, analog and digital systems, neuromorphic circuits, computer science and artificial intelligence
Author : Janusz Kacprzyk
Publisher : Springer
ISBN 13 : 3662435055
Total Pages : 1637 pages
Book Rating : 4.6/5 (624 download)
Download or read book Springer Handbook of Computational Intelligence written by Janusz Kacprzyk and published by Springer. This book was released on 2015-05-28 with total page 1637 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Springer Handbook for Computational Intelligence is the first book covering the basics, the state-of-the-art and important applications of the dynamic and rapidly expanding discipline of computational intelligence. This comprehensive handbook makes readers familiar with a broad spectrum of approaches to solve various problems in science and technology. Possible approaches include, for example, those being inspired by biology, living organisms and animate systems. Content is organized in seven parts: foundations; fuzzy logic; rough sets; evolutionary computation; neural networks; swarm intelligence and hybrid computational intelligence systems. Each Part is supervised by its own Part Editor(s) so that high-quality content as well as completeness are assured.
Author : Boris Kryzhanovsky
Publisher : Springer Nature
ISBN 13 : 3031448650
Total Pages : 505 pages
Book Rating : 4.0/5 (314 download)
Download or read book Advances in Neural Computation, Machine Learning, and Cognitive Research VII written by Boris Kryzhanovsky and published by Springer Nature. This book was released on 2023-11-12 with total page 505 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book describes new theories and applications of artificial neural networks, with a special focus on answering questions in neuroscience, biology and biophysics and cognitive research. It covers a wide range of methods and technologies, including deep neural networks, large-scale neural models, brain–computer interface, signal processing methods, as well as models of perception, studies on emotion recognition, self-organization and many more. The book includes both selected and invited papers presented at the XXV International Conference on Neuroinformatics, held on October 23-27, 2023, in Moscow, Russia.
Author : Jose G. Delgado-Frias
Publisher : Springer Science & Business Media
ISBN 13 : 1461537525
Total Pages : 411 pages
Book Rating : 4.4/5 (615 download)
Download or read book VLSI for Artificial Intelligence and Neural Networks written by Jose G. Delgado-Frias and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 411 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is an edited selection of the papers presented at the International Workshop on VLSI for Artifidal Intelligence and Neural Networks which was held at the University of Oxford in September 1990. Our thanks go to all the contributors and especially to the programme committee for all their hard work. Thanks are also due to the ACM-SIGARCH, the IEEE Computer Society, and the lEE for publicizing the event and to the University of Oxford and SUNY-Binghamton for their active support. We are particularly grateful to Anna Morris, Maureen Doherty and Laura Duffy for coping with the administrative problems. Jose Delgado-Frias Will Moore April 1991 vii PROLOGUE Artificial intelligence and neural network algorithms/computing have increased in complexity as well as in the number of applications. This in tum has posed a tremendous need for a larger computational power than can be provided by conventional scalar processors which are oriented towards numeric and data manipulations. Due to the artificial intelligence requirements (symbolic manipulation, knowledge representation, non-deterministic computations and dynamic resource allocation) and neural network computing approach (non-programming and learning), a different set of constraints and demands are imposed on the computer architectures for these applications.
