Application Of Fpga To Real Time Machine Learning

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Application of FPGA to Real‐Time Machine Learning

Author : Piotr Antonik
Publisher : Springer
ISBN 13 : 3319910531
Total Pages : 171 pages
Book Rating : 4.3/5 (199 download)

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Book Synopsis Application of FPGA to Real‐Time Machine Learning by : Piotr Antonik

Download or read book Application of FPGA to Real‐Time Machine Learning written by Piotr Antonik and published by Springer. This book was released on 2018-05-18 with total page 171 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book lies at the interface of machine learning – a subfield of computer science that develops algorithms for challenging tasks such as shape or image recognition, where traditional algorithms fail – and photonics – the physical science of light, which underlies many of the optical communications technologies used in our information society. It provides a thorough introduction to reservoir computing and field-programmable gate arrays (FPGAs). Recently, photonic implementations of reservoir computing (a machine learning algorithm based on artificial neural networks) have made a breakthrough in optical computing possible. In this book, the author pushes the performance of these systems significantly beyond what was achieved before. By interfacing a photonic reservoir computer with a high-speed electronic device (an FPGA), the author successfully interacts with the reservoir computer in real time, allowing him to considerably expand its capabilities and range of possible applications. Furthermore, the author draws on his expertise in machine learning and FPGA programming to make progress on a very different problem, namely the real-time image analysis of optical coherence tomography for atherosclerotic arteries.

FPGA Frontiers

Author : Nicole Hemsoth
Publisher : Next Platform Press
ISBN 13 : 9780692835463
Total Pages : pages
Book Rating : 4.8/5 (354 download)

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Book Synopsis FPGA Frontiers by : Nicole Hemsoth

Download or read book FPGA Frontiers written by Nicole Hemsoth and published by Next Platform Press. This book was released on 2017-01-16 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: While field programmable gate arrays (FPGAs) are certainly not new, their time to take the market by force did not fully arrive until 2016, at least for a new wave of applications in research, enterprise, and machine learning. With key acquisitions, highly publicized use cases of FPGAs at scale for real-world applications, and momentum to make programming these devices easier, FPGAs found the limelight-and that story is just beginning. Tracing the progression of FPGA use cases, technology developments, and market trends via the compute infrastructure analysis publication, The Next Platform, authors Nicole Hemsoth and Timothy Prickett Morgan pull together the last year in FPGA developments and offer a synthesized, holistic view of where the industry is heading-and where the new application areas will emerge. From the use of these devices in deep learning and machine learning, high performance computing (HPC), and enterprise applications, the range of FPGA acceleration is growing. In this 2017 edition of the book, readers will see the big picture for FPGAs in terms of past, present, and future and be armed with a sense of direction for new applications and innovations on the device and software sides.

Exploring Zynq Mpsoc

Author : Louise H Crockett
Publisher :
ISBN 13 : 9780992978754
Total Pages : 642 pages
Book Rating : 4.9/5 (787 download)

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Book Synopsis Exploring Zynq Mpsoc by : Louise H Crockett

Download or read book Exploring Zynq Mpsoc written by Louise H Crockett and published by . This book was released on 2019-04-11 with total page 642 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book introduces the Zynq MPSoC (Multi-Processor System-on-Chip), an embedded device from Xilinx. The Zynq MPSoC combines a sophisticated processing system that includes ARM Cortex-A53 applications and ARM Cortex-R5 real-time processors, with FPGA programmable logic. As well as guiding the reader through the architecture of the device, design tools and methods are also covered in detail: both the conventional hardware/software co-design approach, and the newer software-defined methodology using Xilinx's SDx development environment. Featured aspects of Zynq MPSoC design include hardware and software development, multiprocessing, safety, security and platform management, and system booting. There are also special features on PYNQ, the Python-based framework for Zynq devices, and machine learning applications. This book should serve as a useful guide for those working with Zynq MPSoC, and equally as a reference for technical managers wishing to gain familiarity with the device and its associated design methodologies.

Explainable Machine Learning Models and Architectures

Author : Suman Lata Tripathi
Publisher : John Wiley & Sons
ISBN 13 : 1394185847
Total Pages : 277 pages
Book Rating : 4.3/5 (941 download)

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Book Synopsis Explainable Machine Learning Models and Architectures by : Suman Lata Tripathi

Download or read book Explainable Machine Learning Models and Architectures written by Suman Lata Tripathi and published by John Wiley & Sons. This book was released on 2023-10-03 with total page 277 pages. Available in PDF, EPUB and Kindle. Book excerpt: EXPLAINABLE MACHINE LEARNING MODELS AND ARCHITECTURES This cutting-edge new volume covers the hardware architecture implementation, the software implementation approach, and the efficient hardware of machine learning applications. Machine learning and deep learning modules are now an integral part of many smart and automated systems where signal processing is performed at different levels. Signal processing in the form of text, images, or video needs large data computational operations at the desired data rate and accuracy. Large data requires more use of integrated circuit (IC) area with embedded bulk memories that further lead to more IC area. Trade-offs between power consumption, delay and IC area are always a concern of designers and researchers. New hardware architectures and accelerators are needed to explore and experiment with efficient machine-learning models. Many real-time applications like the processing of biomedical data in healthcare, smart transportation, satellite image analysis, and IoT-enabled systems have a lot of scope for improvements in terms of accuracy, speed, computational powers, and overall power consumption. This book deals with the efficient machine and deep learning models that support high-speed processors with reconfigurable architectures like graphic processing units (GPUs) and field programmable gate arrays (FPGAs), or any hybrid system. Whether for the veteran engineer or scientist working in the field or laboratory, or the student or academic, this is a must-have for any library.

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

VLSI and Hardware Implementations using Modern Machine Learning Methods

Author : Sandeep Saini
Publisher : CRC Press
ISBN 13 : 1000523845
Total Pages : 292 pages
Book Rating : 4.0/5 (5 download)

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Book Synopsis VLSI and Hardware Implementations using Modern Machine Learning Methods by : Sandeep Saini

Download or read book VLSI and Hardware Implementations using Modern Machine Learning Methods written by Sandeep Saini and published by CRC Press. This book was released on 2021-12-31 with total page 292 pages. Available in PDF, EPUB and Kindle. Book excerpt: Machine learning is a potential solution to resolve bottleneck issues in VLSI via optimizing tasks in the design process. This book aims to provide the latest machine-learning–based methods, algorithms, architectures, and frameworks designed for VLSI design. The focus is on digital, analog, and mixed-signal design techniques, device modeling, physical design, hardware implementation, testability, reconfigurable design, synthesis and verification, and related areas. Chapters include case studies as well as novel research ideas in the given field. Overall, the book provides practical implementations of VLSI design, IC design, and hardware realization using machine learning techniques. Features: Provides the details of state-of-the-art machine learning methods used in VLSI design Discusses hardware implementation and device modeling pertaining to machine learning algorithms Explores machine learning for various VLSI architectures and reconfigurable computing Illustrates the latest techniques for device size and feature optimization Highlights the latest case studies and reviews of the methods used for hardware implementation This book is aimed at researchers, professionals, and graduate students in VLSI, machine learning, electrical and electronic engineering, computer engineering, and hardware systems.

Reservoir Computing

Author : Kohei Nakajima
Publisher : Springer Nature
ISBN 13 : 9811316872
Total Pages : 463 pages
Book Rating : 4.8/5 (113 download)

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Book Synopsis Reservoir Computing by : Kohei Nakajima

Download or read book Reservoir Computing written by Kohei Nakajima and published by Springer Nature. This book was released on 2021-08-05 with total page 463 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is the first comprehensive book about reservoir computing (RC). RC is a powerful and broadly applicable computational framework based on recurrent neural networks. Its advantages lie in small training data set requirements, fast training, inherent memory and high flexibility for various hardware implementations. It originated from computational neuroscience and machine learning but has, in recent years, spread dramatically, and has been introduced into a wide variety of fields, including complex systems science, physics, material science, biological science, quantum machine learning, optical communication systems, and robotics. Reviewing the current state of the art and providing a concise guide to the field, this book introduces readers to its basic concepts, theory, techniques, physical implementations and applications. The book is sub-structured into two major parts: theory and physical implementations. Both parts consist of a compilation of chapters, authored by leading experts in their respective fields. The first part is devoted to theoretical developments of RC, extending the framework from the conventional recurrent neural network context to a more general dynamical systems context. With this broadened perspective, RC is not restricted to the area of machine learning but is being connected to a much wider class of systems. The second part of the book focuses on the utilization of physical dynamical systems as reservoirs, a framework referred to as physical reservoir computing. A variety of physical systems and substrates have already been suggested and used for the implementation of reservoir computing. Among these physical systems which cover a wide range of spatial and temporal scales, are mechanical and optical systems, nanomaterials, spintronics, and quantum many body systems. This book offers a valuable resource for researchers (Ph.D. students and experts alike) and practitioners working in the field of machine learning, artificial intelligence, robotics, neuromorphic computing, complex systems, and physics.

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.

Getting Started with Enterprise Internet of Things: Design Approaches and Software Architecture Models

Author : L. S. Jayashree
Publisher : Springer Nature
ISBN 13 : 3030309452
Total Pages : 142 pages
Book Rating : 4.0/5 (33 download)

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Book Synopsis Getting Started with Enterprise Internet of Things: Design Approaches and Software Architecture Models by : L. S. Jayashree

Download or read book Getting Started with Enterprise Internet of Things: Design Approaches and Software Architecture Models written by L. S. Jayashree and published by Springer Nature. This book was released on 2020-04-16 with total page 142 pages. Available in PDF, EPUB and Kindle. Book excerpt: This novel textbook introduces Enterprise Internet of Things from technology, management and business perspectives, carefully examining enterprise environments through the lens of modernization with the Internet of Things (IoT). It also includes detailed case studies to offer meaningful insights for readers from various disciplines and areas. The book analyzes the ways in which the technology could contribute to the enterprise world in terms of revenue and new business models, and addresses the strategies and principles involved in developing IoT solutions with software engineering practices such as DevOps and Micro services architecture principles. By doing so, it offers readers a clear overview of the power of Internet of Things in building next generation enterprise use cases. The book enables readers to understand the latest opportunities to create new business models in enterprises using the unprecedented level of device connectivity, and the wealth of data generated and information exchange among these devices. As such, it appeals to various user groups, such as engineers trying to solve problems in their own domains using Enterprise IoT, academics interested in gaining a better understanding of applications of IoT in large-scale enterprises, and researchers wanting to contribute to the ever-growing and complex area of IoT.

Machine Learning for Future Fiber-Optic Communication Systems

Author : Alan Pak Tao Lau
Publisher : Academic Press
ISBN 13 : 0323852289
Total Pages : 404 pages
Book Rating : 4.3/5 (238 download)

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Book Synopsis Machine Learning for Future Fiber-Optic Communication Systems by : Alan Pak Tao Lau

Download or read book Machine Learning for Future Fiber-Optic Communication Systems written by Alan Pak Tao Lau and published by Academic Press. This book was released on 2022-02-10 with total page 404 pages. Available in PDF, EPUB and Kindle. Book excerpt: Machine Learning for Future Fiber-Optic Communication Systems provides a comprehensive and in-depth treatment of machine learning concepts and techniques applied to key areas within optical communications and networking, reflecting the state-of-the-art research and industrial practices. The book gives knowledge and insights into the role machine learning-based mechanisms will soon play in the future realization of intelligent optical network infrastructures that can manage and monitor themselves, diagnose and resolve problems, and provide intelligent and efficient services to the end users. With up-to-date coverage and extensive treatment of various important topics related to machine learning for fiber-optic communication systems, this book is an invaluable reference for photonics researchers and engineers. It is also a very suitable text for graduate students interested in ML-based signal processing and networking. Discusses the reasons behind the recent popularity of machine learning (ML) concepts in modern optical communication networks and the why/where/how ML can play a unique role Presents fundamental ML techniques like artificial neural networks (ANNs), support vector machines (SVMs), K-means clustering, expectation-maximization (EM) algorithm, principal component analysis (PCA), independent component analysis (ICA), reinforcement learning, and more Covers advanced deep learning (DL) methods such as deep neural networks (DNNs), convolutional neural networks (CNNs), recurrent neural networks (RNNs), and generative adversarial networks (GANs) Individual chapters focus on ML applications in key areas of optical communications and networking

Machine Learning in Industry

Author : Shubhabrata Datta
Publisher : Springer Nature
ISBN 13 : 3030758478
Total Pages : 202 pages
Book Rating : 4.0/5 (37 download)

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Book Synopsis Machine Learning in Industry by : Shubhabrata Datta

Download or read book Machine Learning in Industry written by Shubhabrata Datta and published by Springer Nature. This book was released on 2021-07-24 with total page 202 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book covers different machine learning techniques such as artificial neural network, support vector machine, rough set theory and deep learning. It points out the difference between the techniques and their suitability for specific applications. This book also describes different applications of machine learning techniques for industrial problems. The book includes several case studies, helping researchers in academia and industries aspiring to use machine learning for solving practical industrial problems.

International Conference on Security, Surveillance and Artificial Intelligence (ICSSAI-2023)

Author : Debasis Chaudhuri
Publisher : CRC Press
ISBN 13 : 1040052487
Total Pages : 468 pages
Book Rating : 4.0/5 (4 download)

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Book Synopsis International Conference on Security, Surveillance and Artificial Intelligence (ICSSAI-2023) by : Debasis Chaudhuri

Download or read book International Conference on Security, Surveillance and Artificial Intelligence (ICSSAI-2023) written by Debasis Chaudhuri and published by CRC Press. This book was released on 2024-05-23 with total page 468 pages. Available in PDF, EPUB and Kindle. Book excerpt: The International Conference on Security, Surveillance & Artificial Intelligence (ICSSAI2023) was held in West Bengal, India during December 1–2, 2023. The conference was organized by the Techno India University, one of the renowned universities in the state of West Bengal which is committed for generating, disseminating and preserving knowledge.

Applied Cryptography and Network Security Workshops

Author : Jianying Zhou
Publisher : Springer Nature
ISBN 13 : 3030816451
Total Pages : 512 pages
Book Rating : 4.0/5 (38 download)

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Book Synopsis Applied Cryptography and Network Security Workshops by : Jianying Zhou

Download or read book Applied Cryptography and Network Security Workshops written by Jianying Zhou and published by Springer Nature. This book was released on 2021-07-21 with total page 512 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the proceedings of the satellite workshops held around the 19th International Conference on Applied Cryptography and Network Security, ACNS 2021, held in Kamakura, Japan, in June 2021. The 26 papers presented in this volume were carefully reviewed and selected from 49 submissions. They stem from the following workshops: AIBlock 2021: Third International Workshop on Application Intelligence and Blockchain Security AIHWS 2021: Second International Workshop on Artificial Intelligence in Hardware Security AIoTS 2021: Third International Workshop on Artificial Intelligence and Industrial IoT Security CIMSS 2021: First International Workshop on Critical Infrastructure and Manufacturing System Security Cloud S&P 2021: Third International Workshop on Cloud Security and Privacy SCI 2021: Second International Workshop on Secure Cryptographic Implementation SecMT 2021: Second International Workshop on Security in Mobile Technologies SiMLA 2021; Third International Workshop on Security in Machine Learning and its Applications Due to the Corona pandemic the workshop was held as a virtual event.

Machine Learning and Deep Learning in Real-Time Applications

Author : Mahrishi, Mehul
Publisher : IGI Global
ISBN 13 : 1799830977
Total Pages : 344 pages
Book Rating : 4.7/5 (998 download)

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Book Synopsis Machine Learning and Deep Learning in Real-Time Applications by : Mahrishi, Mehul

Download or read book Machine Learning and Deep Learning in Real-Time Applications written by Mahrishi, Mehul and published by IGI Global. This book was released on 2020-04-24 with total page 344 pages. Available in PDF, EPUB and Kindle. Book excerpt: Artificial intelligence and its various components are rapidly engulfing almost every professional industry. Specific features of AI that have proven to be vital solutions to numerous real-world issues are machine learning and deep learning. These intelligent agents unlock higher levels of performance and efficiency, creating a wide span of industrial applications. However, there is a lack of research on the specific uses of machine/deep learning in the professional realm. Machine Learning and Deep Learning in Real-Time Applications provides emerging research exploring the theoretical and practical aspects of machine learning and deep learning and their implementations as well as their ability to solve real-world problems within several professional disciplines including healthcare, business, and computer science. Featuring coverage on a broad range of topics such as image processing, medical improvements, and smart grids, this book is ideally designed for researchers, academicians, scientists, industry experts, scholars, IT professionals, engineers, and students seeking current research on the multifaceted uses and implementations of machine learning and deep learning across the globe.

Advanced Machine Learning Technologies and Applications

Author : Aboul Ella Hassanien
Publisher : Springer
ISBN 13 : 3642353266
Total Pages : 606 pages
Book Rating : 4.6/5 (423 download)

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Book Synopsis Advanced Machine Learning Technologies and Applications by : Aboul Ella Hassanien

Download or read book Advanced Machine Learning Technologies and Applications written by Aboul Ella Hassanien and published by Springer. This book was released on 2012-12-03 with total page 606 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the First International Conference on Advanced Machine Learning Technologies and Applications, AMLTA 2012, held in Cairo, Egypt, in December 2012. The 58 full papers presented were carefully reviewed and selected from 99 intial submissions. The papers are organized in topical sections on rough sets and applications, machine learning in pattern recognition and image processing, machine learning in multimedia computing, bioinformatics and cheminformatics, data classification and clustering, cloud computing and recommender systems.

Internet of Things – ICIOT 2018

Author : Dimitrios Georgakopoulos
Publisher : Springer
ISBN 13 : 3319943707
Total Pages : 193 pages
Book Rating : 4.3/5 (199 download)

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Book Synopsis Internet of Things – ICIOT 2018 by : Dimitrios Georgakopoulos

Download or read book Internet of Things – ICIOT 2018 written by Dimitrios Georgakopoulos and published by Springer. This book was released on 2018-06-18 with total page 193 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the proceedings of the International Conference on Internet of Things, ICIOT 2018, held in Seattle, WA, USA, in June 2018. The 13 full papers and 1 short paper presented in this volume was carefully reviewed and selected for inclusion in this book. The contributions are organized in topical sections named: Research Track – Architecture; Research Track – Smart IoT; Application and Industry Track; and Short Paper Track. They deal with research and application innovations in the internet of things services.

Data-Driven Mining, Learning and Analytics for Secured Smart Cities

Author : Chinmay Chakraborty
Publisher : Springer Nature
ISBN 13 : 3030721396
Total Pages : 383 pages
Book Rating : 4.0/5 (37 download)

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Book Synopsis Data-Driven Mining, Learning and Analytics for Secured Smart Cities by : Chinmay Chakraborty

Download or read book Data-Driven Mining, Learning and Analytics for Secured Smart Cities written by Chinmay Chakraborty and published by Springer Nature. This book was released on 2021-04-28 with total page 383 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides information on data-driven infrastructure design, analytical approaches, and technological solutions with case studies for smart cities. This book aims to attract works on multidisciplinary research spanning across the computer science and engineering, environmental studies, services, urban planning and development, social sciences and industrial engineering on technologies, case studies, novel approaches, and visionary ideas related to data-driven innovative solutions and big data-powered applications to cope with the real world challenges for building smart cities.