Download or read book Neuro inspired Computing for Next gen AI Computing Model Architectures and Learning Algorithms written by Angeliki Pantazi and published by Frontiers Media SA. This book was released on 2022-08-29 with total page 160 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Artificial Intelligence in the Age of Neural Networks and Brain Computing written by Robert Kozma and published by Academic Press. This book was released on 2023-10-11 with total page 398 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

Download or read book How to Build a Brain written by Chris Eliasmith and published by Oxford University Press. This book was released on 2013-04-16 with total page 475 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Brain inspired Cognition and Understanding for Next generation AI Computational Models Architectures and Learning Algorithms written by Chenwei Deng and published by Frontiers Media SA. This book was released on 2023-04-19 with total page 223 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Spiking Neural Network Learning Benchmarking Programming and Executing written by Guoqi Li and published by Frontiers Media SA. This book was released on 2020-06-05 with total page 234 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Event Based Neuromorphic Systems written by Shih-Chii Liu and published by John Wiley & Sons. This book was released on 2015-02-16 with total page 440 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Bio inspired Audio Processing Models and Systems written by Shih-Chii Liu and published by Frontiers Media SA. This book was released on 2019-12-05 with total page 200 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Towards Neuroscience Inspired Intelligent Computing Theory Methods and Applications written by Di Wu and published by Frontiers Media SA. This book was released on 2023-04-03 with total page 136 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Neuromorphic Photonic Devices and Applications written by Min Gu and published by Elsevier. This book was released on 2023-12-01 with total page 415 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

Download or read book The Deep Learning Revolution written by Terrence J. Sejnowski and published by MIT Press. This book was released on 2018-10-23 with total page 354 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Efficient Processing of Deep Neural Networks written by Vivienne Sze and published by Springer Nature. This book was released on 2022-05-31 with total page 254 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a structured treatment of the key principles and techniques for enabling efficient processing of deep neural networks (DNNs). DNNs are currently widely used for many artificial intelligence (AI) applications, including computer vision, speech recognition, and robotics. While DNNs deliver state-of-the-art accuracy on many AI tasks, it comes at the cost of high computational complexity. Therefore, techniques that enable efficient processing of deep neural networks to improve key metrics—such as energy-efficiency, throughput, and latency—without sacrificing accuracy or increasing hardware costs are critical to enabling the wide deployment of DNNs in AI systems. The book includes background on DNN processing; a description and taxonomy of hardware architectural approaches for designing DNN accelerators; key metrics for evaluating and comparing different designs; features of DNN processing that are amenable to hardware/algorithm co-design to improve energy efficiency and throughput; and opportunities for applying new technologies. Readers will find a structured introduction to the field as well as formalization and organization of key concepts from contemporary work that provide insights that may spark new ideas.

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.

Download or read book Understanding Machine Learning written by Shai Shalev-Shwartz and published by Cambridge University Press. This book was released on 2014-05-19 with total page 415 pages. Available in PDF, EPUB and Kindle. Book excerpt: Introduces machine learning and its algorithmic paradigms, explaining the principles behind automated learning approaches and the considerations underlying their usage.

Download or read book 30 MACHINE LEARNING ALGORITHMS 2024 Edition written by Diego Rodrigues and published by Diego Rodrigues. This book was released on 2024-11-11 with total page 192 pages. Available in PDF, EPUB and Kindle. Book excerpt: 🚀 TAKE ADVANTAGE OF THE PROMOTIONAL LAUNCH OFFER OF THE YEAR 🚀 Become a master in machine learning with "30 MACHINE LEARNING ALGORITHMS: An Essential Guide for Students and Professionals - 2024 Edition". This book, created by Diego Rodrigues, is indispensable for students, developers, and professionals looking to excel in the dynamic field of artificial intelligence and data science. With a focus on practical applications, you will learn to implement the most powerful algorithms and transform data into valuable insights. Explore essential algorithms such as Linear Regression, Logistic Regression, Decision Trees, Random Forest, SVM, KNN, Naive Bayes, Gradient Boosting, XGBoost, LightGBM, K-Means, DBSCAN, Hierarchical Clustering, PCA, ICA, LDA, Q-Learning, SARSA, DQN, Neural Networks, CNN, RNN, LSTM, GAN, Apriori, FP-Growth, Lasso Regression, Ridge Regression, Elastic Net, and Transformer Neural Networks. With practical examples and detailed explanations, this guide will enable you to master advanced techniques and apply them confidently in real-world projects. This book is more than just a guide; it is your passport to the future of technology. Learn to build predictive models, optimize processes, discover hidden patterns in big data, and much more. Acquire skills that are in high demand and position yourself as a leader in artificial intelligence, data science, and deep learning. Don’t miss the opportunity to elevate your knowledge and stand out in the market. With this guide, you will not only learn but also apply, turning challenges into innovative solutions that will make you shine in the era of digital transformation. 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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 2024-08-01 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.

Download or read book The Perceptron written by Frank Rosenblatt and published by . This book was released on 1958 with total page 290 pages. Available in PDF, EPUB and Kindle. Book excerpt:

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.