Advances In Electromagnetics Empowered By Artificial Intelligence And Deep Learning

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Advances in Electromagnetics Empowered by Artificial Intelligence and Deep Learning

Author : Sawyer D. Campbell
Publisher : John Wiley & Sons
ISBN 13 : 1119853893
Total Pages : 596 pages
Book Rating : 4.1/5 (198 download)

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Book Synopsis Advances in Electromagnetics Empowered by Artificial Intelligence and Deep Learning by : Sawyer D. Campbell

Download or read book Advances in Electromagnetics Empowered by Artificial Intelligence and Deep Learning written by Sawyer D. Campbell and published by John Wiley & Sons. This book was released on 2023-09-26 with total page 596 pages. Available in PDF, EPUB and Kindle. Book excerpt: Authoritative reference on the state of the art in the field with additional coverage of important foundational concepts Advances in Electromagnetics Empowered by Artificial Intelligence and Deep Learning presents cutting-edge research advances in the rapidly growing areas in optical and RF electromagnetic device modeling, simulation, and inverse-design. The text provides a comprehensive treatment of the field on subjects ranging from fundamental theoretical principles and new technological developments to state-of-the-art device design, as well as examples encompassing a wide range of related sub-areas. The content of the book covers all-dielectric and metallodielectric optical metasurface deep learning-accelerated inverse-design, deep neural networks for inverse scattering, applications of deep learning for advanced antenna design, and other related topics. To aid in reader comprehension, each chapter contains 10-15 illustrations, including prototype photos, line graphs, and electric field plots. Contributed to by leading research groups in the field, sample topics covered in Advances in Electromagnetics Empowered by Artificial Intelligence and Deep Learning include: Optical and photonic design, including generative machine learning for photonic design and inverse design of electromagnetic systems RF and antenna design, including artificial neural networks for parametric electromagnetic modeling and optimization and analysis of uniform and non-uniform antenna arrays Inverse scattering, target classification, and other applications, including deep learning for high contrast inverse scattering of electrically large structures Advances in Electromagnetics Empowered by Artificial Intelligence and Deep Learning is a must-have resource on the topic for university faculty, graduate students, and engineers within the fields of electromagnetics, wireless communications, antenna/RF design, and photonics, as well as researchers at large defense contractors and government laboratories.

Advances in Electromagnetics Empowered by Artificial Intelligence and Deep Learning

Author : Sawyer D. Campbell
Publisher : John Wiley & Sons
ISBN 13 : 1119853915
Total Pages : 596 pages
Book Rating : 4.1/5 (198 download)

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Book Synopsis Advances in Electromagnetics Empowered by Artificial Intelligence and Deep Learning by : Sawyer D. Campbell

Download or read book Advances in Electromagnetics Empowered by Artificial Intelligence and Deep Learning written by Sawyer D. Campbell and published by John Wiley & Sons. This book was released on 2023-08-03 with total page 596 pages. Available in PDF, EPUB and Kindle. Book excerpt: Advances in Electromagnetics Empowered by Artificial Intelligence and Deep Learning Authoritative reference on the state of the art in the field with additional coverage of important foundational concepts Advances in Electromagnetics Empowered by Artificial Intelligence and Deep Learning presents cutting-edge research advances in the rapidly growing areas in optical and RF electromagnetic device modeling, simulation, and inverse-design. The text provides a comprehensive treatment of the field on subjects ranging from fundamental theoretical principles and new technological developments to state-of-the-art device design, as well as examples encompassing a wide range of related sub-areas. The content of the book covers all-dielectric and metallodielectric optical metasurface deep learning-accelerated inverse-design, deep neural networks for inverse scattering, applications of deep learning for advanced antenna design, and other related topics. To aid in reader comprehension, each chapter contains 10-15 illustrations, including prototype photos, line graphs, and electric field plots. Contributed to by leading research groups in the field, sample topics covered in Advances in Electromagnetics Empowered by Artificial Intelligence and Deep Learning include: Optical and photonic design, including generative machine learning for photonic design and inverse design of electromagnetic systems RF and antenna design, including artificial neural networks for parametric electromagnetic modeling and optimization and analysis of uniform and non-uniform antenna arrays Inverse scattering, target classification, and other applications, including deep learning for high contrast inverse scattering of electrically large structures Advances in Electromagnetics Empowered by Artificial Intelligence and Deep Learning is a must-have resource on the topic for university faculty, graduate students, and engineers within the fields of electromagnetics, wireless communications, antenna/RF design, and photonics, as well as researchers at large defense contractors and government laboratories.

Theory and Computation of Electromagnetic Fields in Layered Media

Author : Vladimir Okhmatovski
Publisher : John Wiley & Sons
ISBN 13 : 1119763193
Total Pages : 756 pages
Book Rating : 4.1/5 (197 download)

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Book Synopsis Theory and Computation of Electromagnetic Fields in Layered Media by : Vladimir Okhmatovski

Download or read book Theory and Computation of Electromagnetic Fields in Layered Media written by Vladimir Okhmatovski and published by John Wiley & Sons. This book was released on 2024-04-30 with total page 756 pages. Available in PDF, EPUB and Kindle. Book excerpt: Explore the algorithms and numerical methods used to compute electromagnetic fields in multi-layered media In Theory and Computation of Electromagnetic Fields in Layered Media, two distinguished electrical engineering researchers deliver a detailed and up-to-date overview of the theory and numerical methods used to determine electromagnetic fields in layered media. The book begins with an introduction to Maxwell’s equations, the fundamentals of electromagnetic theory, and concepts and definitions relating to Green’s function. It then moves on to solve canonical problems in vertical and horizontal dipole radiation, describe Method of Moments schemes, discuss integral equations governing electromagnetic fields, and explains the Michalski-Zheng theory of mixed-potential Green’s function representation in multi-layered media. Chapters on the evaluation of Sommerfeld integrals, procedures for far field evaluation, and the theory and application of hierarchical matrices are also included, along with: A thorough introduction to free-space Green’s functions, including the delta-function model for point charge and dipole current Comprehensive explorations of the traditional form of layered medium Green’s function in three dimensions Practical discussions of electro-quasi-static and magneto-quasi-static fields in layered media, including electrostatic fields in two and three dimensions In-depth examinations of the rational function fitting method, including direct spectra fitting with VECTFIT algorithms Perfect for scholars and students of electromagnetic analysis in layered media, Theory and Computation of Electromagnetic Fields in Layered Media will also earn a place in the libraries of CAD industry engineers and software developers working in the area of computational electromagnetics.

Deterministic and Stochastic Modeling in Computational Electromagnetics

Author : Dragan Poljak
Publisher : John Wiley & Sons
ISBN 13 : 1119989248
Total Pages : 580 pages
Book Rating : 4.1/5 (199 download)

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Book Synopsis Deterministic and Stochastic Modeling in Computational Electromagnetics by : Dragan Poljak

Download or read book Deterministic and Stochastic Modeling in Computational Electromagnetics written by Dragan Poljak and published by John Wiley & Sons. This book was released on 2023-12-07 with total page 580 pages. Available in PDF, EPUB and Kindle. Book excerpt: Deterministic and Stochastic Modeling in Computational Electromagnetics Help protect your network with this important reference work on cyber security Deterministic computational models are those for which all inputs are precisely known, whereas stochastic modeling reflects uncertainty or randomness in one or more of the data inputs. Many problems in computational engineering therefore require both deterministic and stochastic modeling to be used in parallel, allowing for different degrees of confidence and incorporating datasets of different kinds. In particular, non-intrusive stochastic methods can be easily combined with widely used deterministic approaches, enabling this more robust form of data analysis to be applied to a range of computational challenges. Deterministic and Stochastic Modeling in Computational Electromagnetics provides a rare treatment of parallel deterministic–stochastic computational modeling and its beneficial applications. Unlike other works of its kind, which generally treat deterministic and stochastic modeling in isolation from one another, it aims to demonstrate the usefulness of a combined approach and present particular use-cases in which such an approach is clearly required. It offers a non-intrusive stochastic approach which can be incorporated with minimal effort into virtually all existing computational models. Readers will also find: A range of specific examples demonstrating the efficiency of deterministic–stochastic modeling Computational examples of successful applications including ground penetrating radars (GPR), radiation from 5G systems, transcranial magnetic and electric stimulation (TMS and TES), and more Introduction to fundamental principles in field theory to ground the discussion of computational modeling Deterministic and Stochastic Modeling in Computational Electromagnetics is a valuable reference for researchers, including graduate and undergraduate students, in computational electromagnetics, as well as to multidisciplinary researchers, engineers, physicists, and mathematicians.

Empowering Artificial Intelligence Through Machine Learning

Author : Nedunchezhian Raju
Publisher : Apple Academic Press
ISBN 13 : 9781774638125
Total Pages : pages
Book Rating : 4.6/5 (381 download)

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Book Synopsis Empowering Artificial Intelligence Through Machine Learning by : Nedunchezhian Raju

Download or read book Empowering Artificial Intelligence Through Machine Learning written by Nedunchezhian Raju and published by Apple Academic Press. This book was released on 2022 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: This new volume, Empowering Artificial intelligence Through Machine Learning: New Advances and Applications, discusses various new applications of machine learning, a subset of the field of artificial intelligence. Artificial intelligence is considered to be the next-big-game changer in research and technology, The volume looks at how computing has enabled machines to learn, making machine and tools become smarter in many sectors, including science and engineering, healthcare, finance, education, gaming, security, and even agriculture, plus many more areas. Topics include techniques and methods in artificial intelligence for making machines intelligent, machine learning in healthcare, using machine learning for credit card fraud detection, using artificial intelligence in education using gaming and automatization with courses and outcomes mapping, and much more. The book will be valuable to professionals, faculty, and students in electronics and communication engineering, telecommunication engineering, network engineering, computer science and information technology.

Convergence of Deep Learning and Artificial Intelligence in Internet of Things

Author : Ajay Rana
Publisher : CRC Press
ISBN 13 : 1000822087
Total Pages : 329 pages
Book Rating : 4.0/5 (8 download)

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Book Synopsis Convergence of Deep Learning and Artificial Intelligence in Internet of Things by : Ajay Rana

Download or read book Convergence of Deep Learning and Artificial Intelligence in Internet of Things written by Ajay Rana and published by CRC Press. This book was released on 2022-12-20 with total page 329 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book covers advances and applications of smart technologies including the Internet of Things (IoT), artificial intelligence, and deep learning in areas such as manufacturing, production, renewable energy, and healthcare. It also covers wearable and implantable biomedical devices for healthcare monitoring, smart surveillance, and monitoring applications such as the use of an autonomous drone for disaster management and rescue operations. It will serve as an ideal reference text for senior undergraduate, graduate students, and academic researchers in the areas such as electrical engineering, electronics and communications engineering, computer engineering, and information technology. • Covers concepts, theories, and applications of artificial intelligence and deep learning, from the perspective of the Internet of Things. • Discusses powers predictive analysis, predictive maintenance, and automated processes for making manufacturing plants more efficient, profitable, and safe. • Explores the importance of blockchain technology in the Internet of Things security issues. • Discusses key deep learning concepts including trust management, identity management, security threats, access control, and privacy. • Showcases the importance of intelligent algorithms for cloud-based Internet of Things applications. This text emphasizes the importance of innovation and improving the profitability of manufacturing plants using smart technologies such as artificial intelligence, deep learning, and the Internet of Things. It further discusses applications of smart technologies in diverse sectors such as agriculture, smart home, production, manufacturing, transport, and healthcare.

Practical Design for Electromagnetic Compatibility

Author : Rocco F. Ficchi
Publisher :
ISBN 13 :
Total Pages : 280 pages
Book Rating : 4.3/5 (91 download)

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Book Synopsis Practical Design for Electromagnetic Compatibility by : Rocco F. Ficchi

Download or read book Practical Design for Electromagnetic Compatibility written by Rocco F. Ficchi and published by . This book was released on 1971 with total page 280 pages. Available in PDF, EPUB and Kindle. Book excerpt: For RFI/EMC engineers, electronic designers, project engineers and others in aerospace and other industries.

Deep Neural Network Applications

Author : Hasmik Osipyan
Publisher : CRC Press
ISBN 13 : 0429556209
Total Pages : 158 pages
Book Rating : 4.4/5 (295 download)

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Book Synopsis Deep Neural Network Applications by : Hasmik Osipyan

Download or read book Deep Neural Network Applications written by Hasmik Osipyan and published by CRC Press. This book was released on 2022-04-28 with total page 158 pages. Available in PDF, EPUB and Kindle. Book excerpt: The world is on the verge of fully ushering in the fourth industrial revolution, of which artificial intelligence (AI) is the most important new general-purpose technology. Like the steam engine that led to the widespread commercial use of driving machineries in the industries during the first industrial revolution; the internal combustion engine that gave rise to cars, trucks, and airplanes; electricity that caused the second industrial revolution through the discovery of direct and alternating current; and the Internet, which led to the emergence of the information age, AI is a transformational technology. It will cause a paradigm shift in the way’s problems are solved in every aspect of our lives, and, from it, innovative technologies will emerge. AI is the theory and development of machines that can imitate human intelligence in tasks such as visual perception, speech recognition, decision-making, and human language translation. This book provides a complete overview on the deep learning applications and deep neural network architectures. It also gives an overview on most advanced future-looking fundamental research in deep learning application in artificial intelligence. Research overview includes reasoning approaches, problem solving, knowledge representation, planning, learning, natural language processing, perception, motion and manipulation, social intelligence and creativity. It will allow the reader to gain a deep and broad knowledge of the latest engineering technologies of AI and Deep Learning and is an excellent resource for academic research and industry applications.

Lateral Electromagnetic Waves

Author : Ronold W.P. King
Publisher : Springer Science & Business Media
ISBN 13 : 1461391741
Total Pages : 771 pages
Book Rating : 4.4/5 (613 download)

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Book Synopsis Lateral Electromagnetic Waves by : Ronold W.P. King

Download or read book Lateral Electromagnetic Waves written by Ronold W.P. King and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 771 pages. Available in PDF, EPUB and Kindle. Book excerpt: The propagation of waves along and across the boundary between two media with different characteristic velocities is much more complicated when the source is on or near the boundary than when it is far away and the incident waves are plane. Examples of waves generated by localized sources near a boundary are the electromagnetic waves from the currents in a dipole on the surface of the earth and the seismic waves from a slip event in a fault in the earth's crust like the San Andreas fault in California. Both involve a type of surface wave that is called a lateral wave in electro magnetics and a head wave in seismology. Since the two are analogous and the latter is more easily visualized, it is conveniently used here to introduce and describe this important type of surface wave using the data of Y. Ben Zion and P. Malin ("San Andreas Fault Zone Head Waves Near Parkfield, CA," Science 251, 1592-1594, 29 March 1991).

Artificial Intelligence For Science: A Deep Learning Revolution

Author : Alok Choudhary
Publisher : World Scientific
ISBN 13 : 9811265682
Total Pages : 803 pages
Book Rating : 4.8/5 (112 download)

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Book Synopsis Artificial Intelligence For Science: A Deep Learning Revolution by : Alok Choudhary

Download or read book Artificial Intelligence For Science: A Deep Learning Revolution written by Alok Choudhary and published by World Scientific. This book was released on 2023-03-21 with total page 803 pages. Available in PDF, EPUB and Kindle. Book excerpt: This unique collection introduces AI, Machine Learning (ML), and deep neural network technologies leading to scientific discovery from the datasets generated both by supercomputer simulation and by modern experimental facilities.Huge quantities of experimental data come from many sources — telescopes, satellites, gene sequencers, accelerators, and electron microscopes, including international facilities such as the Large Hadron Collider (LHC) at CERN in Geneva and the ITER Tokamak in France. These sources generate many petabytes moving to exabytes of data per year. Extracting scientific insights from these data is a major challenge for scientists, for whom the latest AI developments will be essential.The timely handbook benefits professionals, researchers, academics, and students in all fields of science and engineering as well as AI, ML, and neural networks. Further, the vision evident in this book inspires all those who influence or are influenced by scientific progress.

Artificial Intelligence

Author : Luis Carlos Rabelo Mendizabal
Publisher :
ISBN 13 : 9781536126778
Total Pages : 0 pages
Book Rating : 4.1/5 (267 download)

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Book Synopsis Artificial Intelligence by : Luis Carlos Rabelo Mendizabal

Download or read book Artificial Intelligence written by Luis Carlos Rabelo Mendizabal and published by . This book was released on 2017-11 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: After decades of basic research and more promises than impressive applications, artificial intelligence (AI) is starting to deliver benefits. A convergence of advances is motivating this new surge of AI development and applications. Computer capability as it has evolved from high throughput and high performance computing systems is increasing. AI models and operations research adaptations are becoming more mature, and the world is breeding big data not only from the web and social media but also from the Internet of Things. Organizations around the world have been realizing that there are substantial performance gains and increases in productivity for the use of AI and predictive analytics techniques. Their use is bringing a new era of breakthrough innovation and opportunities. This book, compiles research insights and applications in diverse areas such as manufacturing, supply chain management, pricing, autonomous vehicles, healthcare, ecommerce, and aeronautics. Using classical and advanced tools in AI such as deep learning, particle swarm optimization, support vector machines and genetic programming among others. This is a very distinctive book which discusses important applications using a variety of paradigms from AI and outlines some of the research to be performed. The work supersedes similar books that do not cover as diversified a set of sophisticated applications. The authors present a comprehensive and articulated view of recent developments, identifies the applications gap by quoting from the experience of experts, and details suggested research areas. Artificial Intelligence: Advances in Research and Applications guides the reader through an intuitive understanding of the methodologies and tools for building and modeling intelligent systems. The book's coverage is broad, starting with clustering techniques with unsupervised ensemble learning, where the optimal combination strategy of individual partitions is robust in comparison to the selection of an algorithmic clustering pool. This is followed by a case in a parallel-distributed simulator using deep learning for its configuration. Chapter Three presents a case for autonomous vehicles. Chapter Four discusses the novel use of genetic algorithms with support vector machines. Chapters Five through Thirteen focus on the applications. The book discusses how the use of AI can allow for productivity development and other benefits not just for businesses, but also for economies. Finally, you can find an interesting investigation of the transhuman dimension of AI.

Methods & Techniques in Deep Learning

Author : Avik Santra
Publisher : John Wiley & Sons
ISBN 13 : 111991065X
Total Pages : 340 pages
Book Rating : 4.1/5 (199 download)

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Book Synopsis Methods & Techniques in Deep Learning by : Avik Santra

Download or read book Methods & Techniques in Deep Learning written by Avik Santra and published by John Wiley & Sons. This book was released on 2022-12-13 with total page 340 pages. Available in PDF, EPUB and Kindle. Book excerpt: Introduces multiple state-of-the-art deep learning architectures for mmwave radar in a variety of advanced applications Methods and Techniques in Deep Learning: Advancements in mmWave Radar Solutions provides a timely and authoritative overview of the use of artificial intelligence (AI)-based processing for various mmwave radar applications. Focusing on practical deep learning techniques, this comprehensive volume explains the fundamentals of deep learning, reviews cutting-edge deep metric learning techniques, describes different typologies of reinforcement learning (RL) algorithms, highlights how domain adaptation (DA) can be used for improving the performance of machine learning (ML) algorithms, and more. Throughout the book, readers are exposed to product-ready deep learning solutions while learning skills that are relevant for building any industrial-grade, sensor-based deep learning solution. A team of authors with more than 70 filed patents and 100 published papers on AI and sensor processing illustrate how deep learning is enabling a range of advanced industrial, consumer, and automotive applications of mmwave radars. In-depth chapters cover topics including multi-modal deep learning approaches, the elemental blocks required to formulate Bayesian deep learning, how domain adaptation (DA) can be used for improving the performance of machine learning algorithms, and geometric deep learning are used for processing point clouds. In addition, the book: Discusses various advanced applications and how their respective challenges have been addressed using different deep learning architectures and algorithms Describes deep learning in the context of computer vision, natural language processing, sensor processing, and mmwave radar sensors Demonstrates how deep parametric learning reduces the number of trainable parameters and improves the data flow Presents several human-machine interface (HMI) applications such as gesture recognition, human activity classification, human localization and tracking in-cabin automotive occupancy sensing Methods and Techniques in Deep Learning: Advancements in mmWave Radar Solutions is an invaluable resource for industry professionals, researchers, and graduate students working in systems engineering, signal processing, sensors, data science and AI.

Deep Learning

Author : John D. Kelleher
Publisher : MIT Press
ISBN 13 : 026235490X
Total Pages : 296 pages
Book Rating : 4.2/5 (623 download)

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Book Synopsis Deep Learning by : John D. Kelleher

Download or read book Deep Learning written by John D. Kelleher and published by MIT Press. This book was released on 2019-09-10 with total page 296 pages. Available in PDF, EPUB and Kindle. Book excerpt: An accessible introduction to the artificial intelligence technology that enables computer vision, speech recognition, machine translation, and driverless cars. Deep learning is an artificial intelligence technology that enables computer vision, speech recognition in mobile phones, machine translation, AI games, driverless cars, and other applications. When we use consumer products from Google, Microsoft, Facebook, Apple, or Baidu, we are often interacting with a deep learning system. In this volume in the MIT Press Essential Knowledge series, computer scientist John Kelleher offers an accessible and concise but comprehensive introduction to the fundamental technology at the heart of the artificial intelligence revolution. Kelleher explains that deep learning enables data-driven decisions by identifying and extracting patterns from large datasets; its ability to learn from complex data makes deep learning ideally suited to take advantage of the rapid growth in big data and computational power. Kelleher also explains some of the basic concepts in deep learning, presents a history of advances in the field, and discusses the current state of the art. He describes the most important deep learning architectures, including autoencoders, recurrent neural networks, and long short-term networks, as well as such recent developments as Generative Adversarial Networks and capsule networks. He also provides a comprehensive (and comprehensible) introduction to the two fundamental algorithms in deep learning: gradient descent and backpropagation. Finally, Kelleher considers the future of deep learning—major trends, possible developments, and significant challenges.

Convergence of Deep Learning and Internet of Things: Computing and Technology

Author : Kavitha, T.
Publisher : IGI Global
ISBN 13 : 166846277X
Total Pages : 371 pages
Book Rating : 4.6/5 (684 download)

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Book Synopsis Convergence of Deep Learning and Internet of Things: Computing and Technology by : Kavitha, T.

Download or read book Convergence of Deep Learning and Internet of Things: Computing and Technology written by Kavitha, T. and published by IGI Global. This book was released on 2022-12-19 with total page 371 pages. Available in PDF, EPUB and Kindle. Book excerpt: Digital technology has enabled a number of internet-enabled devices that generate huge volumes of data from different systems. This large amount of heterogeneous data requires efficient data collection, processing, and analytical methods. Deep Learning is one of the latest efficient and feasible solutions that enable smart devices to function independently with a decision-making support system. Convergence of Deep Learning and Internet of Things: Computing and Technology contributes to technology and methodology perspectives in the incorporation of deep learning approaches in solving a wide range of issues in the IoT domain to identify, optimize, predict, forecast, and control emerging IoT systems. Covering topics such as data quality, edge computing, and attach detection and prediction, this premier reference source is a comprehensive resource for electricians, communications specialists, mechanical engineers, civil engineers, computer scientists, students and educators of higher education, librarians, researchers, and academicians.

Hardware Accelerator Systems for Artificial Intelligence and Machine Learning

Author :
Publisher : Academic Press
ISBN 13 : 0128231246
Total Pages : 416 pages
Book Rating : 4.1/5 (282 download)

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Book Synopsis Hardware Accelerator Systems for Artificial Intelligence and Machine Learning by :

Download or read book Hardware Accelerator Systems for Artificial Intelligence and Machine Learning written by and published by Academic Press. This book was released on 2021-03-28 with total page 416 pages. Available in PDF, EPUB and Kindle. Book excerpt: Hardware Accelerator Systems for Artificial Intelligence and Machine Learning, Volume 122 delves into arti?cial Intelligence and the growth it has seen with the advent of Deep Neural Networks (DNNs) and Machine Learning. Updates in this release include chapters on Hardware accelerator systems for artificial intelligence and machine learning, Introduction to Hardware Accelerator Systems for Artificial Intelligence and Machine Learning, Deep Learning with GPUs, Edge Computing Optimization of Deep Learning Models for Specialized Tensor Processing Architectures, Architecture of NPU for DNN, Hardware Architecture for Convolutional Neural Network for Image Processing, FPGA based Neural Network Accelerators, and much more. Updates on new information on the architecture of GPU, NPU and DNN Discusses In-memory computing, Machine intelligence and Quantum computing Includes sections on Hardware Accelerator Systems to improve processing efficiency and performance

Spectral Logic and Its Applications for the Design of Digital Devices

Author : Mark G. Karpovsky
Publisher : John Wiley & Sons
ISBN 13 : 047028921X
Total Pages : 642 pages
Book Rating : 4.4/5 (72 download)

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Book Synopsis Spectral Logic and Its Applications for the Design of Digital Devices by : Mark G. Karpovsky

Download or read book Spectral Logic and Its Applications for the Design of Digital Devices written by Mark G. Karpovsky and published by John Wiley & Sons. This book was released on 2008-07-14 with total page 642 pages. Available in PDF, EPUB and Kindle. Book excerpt: Spectral techniques facilitate the design and testing of today's increasingly complex digital devices There is heightened interest in spectral techniques for the design of digital devices dictated by ever increasing demands on technology that often cannot be met by classical approaches. Spectral methods provide a uniform and consistent theoretic environment for recent achievements in this area, which appear divergent in many other approaches. Spectral Logic and Its Applications for the Design of Digital Devices gives readers a foundation for further exploration of abstract harmonic analysis over finite groups in the analysis, design, and testing of digital devices. After an introduction, this book provides the essential mathematical background for discussing spectral methods. It then delves into spectral logic and its applications, covering: * Walsh, Haar, arithmetic transform, Reed-Muller transform for binary-valued functions and Vilenkin-Chrestenson transform, generalized Haar, and other related transforms for multiple-valued functions * Polynomial expressions and decision diagram representations for switching and multiple-value functions * Spectral analysis of Boolean functions * Spectral synthesis and optimization of combinational and sequential devices * Spectral methods in analysis and synthesis of reliable devices * Spectral techniques for testing computer hardware This is the authoritative reference for computer science and engineering professionals and researchers with an interest in spectral methods of representing discrete functions and related applications in the design and testing of digital devices. It is also an excellent text for graduate students in courses covering spectral logic and its applications.

Artificial Intelligence

Author : Christina Ahmet
Publisher : Shockwave Publishing via PublishDrive
ISBN 13 :
Total Pages : 69 pages
Book Rating : 4.:/5 (661 download)

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Book Synopsis Artificial Intelligence by : Christina Ahmet

Download or read book Artificial Intelligence written by Christina Ahmet and published by Shockwave Publishing via PublishDrive. This book was released on 2018-11-20 with total page 69 pages. Available in PDF, EPUB and Kindle. Book excerpt: Currently, Artificial Intelligence (AI) lives amongst the human population. They reside in smartphones. They help people find content on the internet. They learn the behavior of their owners and put out relevant, interesting content to enhance their owner's experience while they are browsing on the internet. In this book you will learn all about Artificial Intelligence and how it will affect your life in the near future. Learn exactly what Artificial Intelligence is Machine Learning AI and The Internet Of Things Opportunities for Artificial Intelligence Intelligent IoT and much much more!