Neuro-inspired Computing for Next-gen AI: Computing Model, Architectures and Learning Algorithms PDF Download
Are you looking for read ebook online? Search for your book and save it on your Kindle device, PC, phones or tablets. Download Neuro-inspired Computing for Next-gen AI: Computing Model, Architectures and Learning Algorithms PDF full book. Access full book title Neuro-inspired Computing for Next-gen AI: Computing Model, Architectures and Learning Algorithms by Angeliki Pantazi. Download full books in PDF and EPUB format.
Author: Angeliki Pantazi
Publisher: Frontiers Media SA
ISBN: 2889768562
Category : Science
Languages : en
Pages : 160
Get Book Here
Book Description
Author: Angeliki Pantazi
Publisher: Frontiers Media SA
ISBN: 2889768562
Category : Science
Languages : en
Pages : 160
Get Book Here
Book Description
Author: Robert Kozma
Publisher: Academic Press
ISBN: 0323958168
Category : Computers
Languages : en
Pages : 398
Get Book Here
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
Author: Chris Eliasmith
Publisher: Oxford University Press
ISBN: 0199794693
Category : Psychology
Languages : en
Pages : 475
Get Book Here
Book Description
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.
Author: Chenwei Deng
Publisher: Frontiers Media SA
ISBN: 2832521169
Category : Science
Languages : en
Pages : 223
Get Book Here
Book Description
Author: Guoqi Li
Publisher: Frontiers Media SA
ISBN: 2889637670
Category :
Languages : en
Pages : 234
Get Book Here
Book Description
Author: Shih-Chii Liu
Publisher: John Wiley & Sons
ISBN: 0470018496
Category : Technology & Engineering
Languages : en
Pages : 440
Get Book Here
Book Description
Neuromorphic electronic engineering takes its inspiration from the functioning of nervous systems to build more power efficient electronic sensors and processors. Event-based neuromorphic systems are inspired by the brain's efficient data-driven communication design, which is key to its quick responses and remarkable capabilities. This cross-disciplinary text establishes how circuit building blocks are combined in architectures to construct complete systems. These include vision and auditory sensors as well as neuronal processing and learning circuits that implement models of nervous systems. Techniques for building multi-chip scalable systems are considered throughout the book, including methods for dealing with transistor mismatch, extensive discussions of communication and interfacing, and making systems that operate in the real world. The book also provides historical context that helps relate the architectures and circuits to each other and that guides readers to the extensive literature. Chapters are written by founding experts and have been extensively edited for overall coherence. This pioneering text is an indispensable resource for practicing neuromorphic electronic engineers, advanced electrical engineering and computer science students and researchers interested in neuromorphic systems. Key features: Summarises the latest design approaches, applications, and future challenges in the field of neuromorphic engineering. Presents examples of practical applications of neuromorphic design principles. Covers address-event communication, retinas, cochleas, locomotion, learning theory, neurons, synapses, floating gate circuits, hardware and software infrastructure, algorithms, and future challenges.
Author: Shih-Chii Liu
Publisher: Frontiers Media SA
ISBN: 2889632326
Category :
Languages : en
Pages : 200
Get Book Here
Book Description
Neurophysiology and biology provide useful starting points to help us understand and build better audio processing systems. The papers in this special issue address hardware implementations, spiking networks, sound identification, and attention decoding.
Author: Di Wu
Publisher: Frontiers Media SA
ISBN: 2832519172
Category : Science
Languages : en
Pages : 136
Get Book Here
Book Description
Author: Min Gu
Publisher: Elsevier
ISBN: 0323972608
Category : Technology & Engineering
Languages : en
Pages : 415
Get Book Here
Book Description
Neuromorphic Photonic Devices and Applications synthesizes the most critical advances in photonic neuromorphic models, photonic material platforms and accelerators for neuromorphic computing. The book discusses fields and applications that can leverage these new platforms. A brief review of the historical development of the field is followed by a discussion of the emerging 2D photonic materials platforms and recent work in implementing neuromorphic models and 3D neuromorphic systems. The application of artificial intelligence (AI), such as neuromorphic models to inverse design neuromorphic materials and devices and predict performance challenges is discussed throughout. Finally, a comprehensive overview of the applications of neuromorphic photonic technologies and the challenges, opportunities and future prospects is discussed, making the book suitable for researchers and practitioners in academia and R&D in the multidisciplinary field of photonics. - Includes overview of primary scientific concepts for the research topic of neuromorphic photonics such as neurons as computational units, artificial intelligence, machine learning and neuromorphic models - Reviews the latest advances in photonic materials, device platforms and enabling technology drivers of neuromorphic photonics - Discusses potential applications in computing and optical communications
Author: Terrence J. Sejnowski
Publisher: MIT Press
ISBN: 026203803X
Category : Computers
Languages : en
Pages : 354
Get Book Here
Book Description
How deep learning—from Google Translate to driverless cars to personal cognitive assistants—is changing our lives and transforming every sector of the economy. The deep learning revolution has brought us driverless cars, the greatly improved Google Translate, fluent conversations with Siri and Alexa, and enormous profits from automated trading on the New York Stock Exchange. Deep learning networks can play poker better than professional poker players and defeat a world champion at Go. In this book, Terry Sejnowski explains how deep learning went from being an arcane academic field to a disruptive technology in the information economy. Sejnowski played an important role in the founding of deep learning, as one of a small group of researchers in the 1980s who challenged the prevailing logic-and-symbol based version of AI. The new version of AI Sejnowski and others developed, which became deep learning, is fueled instead by data. Deep networks learn from data in the same way that babies experience the world, starting with fresh eyes and gradually acquiring the skills needed to navigate novel environments. Learning algorithms extract information from raw data; information can be used to create knowledge; knowledge underlies understanding; understanding leads to wisdom. Someday a driverless car will know the road better than you do and drive with more skill; a deep learning network will diagnose your illness; a personal cognitive assistant will augment your puny human brain. It took nature many millions of years to evolve human intelligence; AI is on a trajectory measured in decades. Sejnowski prepares us for a deep learning future.
