Neuromorphic Computing Systems for Industry 4.0 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 Neuromorphic Computing Systems for Industry 4.0 PDF full book. Access full book title Neuromorphic Computing Systems for Industry 4.0 by Dhanasekar, S.. Download full books in PDF and EPUB format.
Author: Dhanasekar, S. Publisher: IGI Global ISBN: 1668465981 Category : Computers Languages : en Pages : 400
Book Description
As artificial intelligence (AI) processing moves from the cloud to the edge of the network, battery-powered and deeply embedded devices are challenged to perform AI functions such as computer vision and voice recognition. Microchip Technology Inc., via its Silicon Storage Technology (SST) subsidiary, is addressing this challenge by significantly reducing power with its analog memory technology, the memBrain Memory Solution. The memBrain solution is being adopted by today’s companies looking to advance machine learning capacities in edge devices. Due to its ability to significantly reduce power, this analog in-memory computer solution is ideal for an AI application. Neuromorphic Computing Systems for Industry 4.0 covers the available literature in the field of neural computing-based microchip technology. It provides further research opportunities in this dynamic field. Covering topics such as emotion recognition, biometric authentication, and neural network protection, this premier reference source is an essential resource for technology developers, computer scientists, engineers, students and educators of higher education, librarians, researchers, and academicians.
Author: Dhanasekar, S. Publisher: IGI Global ISBN: 1668465981 Category : Computers Languages : en Pages : 400
Book Description
As artificial intelligence (AI) processing moves from the cloud to the edge of the network, battery-powered and deeply embedded devices are challenged to perform AI functions such as computer vision and voice recognition. Microchip Technology Inc., via its Silicon Storage Technology (SST) subsidiary, is addressing this challenge by significantly reducing power with its analog memory technology, the memBrain Memory Solution. The memBrain solution is being adopted by today’s companies looking to advance machine learning capacities in edge devices. Due to its ability to significantly reduce power, this analog in-memory computer solution is ideal for an AI application. Neuromorphic Computing Systems for Industry 4.0 covers the available literature in the field of neural computing-based microchip technology. It provides further research opportunities in this dynamic field. Covering topics such as emotion recognition, biometric authentication, and neural network protection, this premier reference source is an essential resource for technology developers, computer scientists, engineers, students and educators of higher education, librarians, researchers, and academicians.
Author: Ashish Kumar Luhach Publisher: Engineering Science Reference ISBN: 9781799851011 Category : Artificial intelligence Languages : en Pages : 315
Book Description
"This book focuses upon the recent advances in the realization of Artificial Intelligence-based approaches towards affecting secure Cyber-Physical Systems. It features contributions pertaining to this multidisciplinary paradigm, in particular, in its application to building sustainable space by investigating state-of-art research issues, applications and achievements in the field of Computational Intelligence Paradigms for Cyber-Physical Systems"--
Author: Leon O. Chua Publisher: Springer Nature ISBN: 3030905829 Category : Technology & Engineering Languages : en Pages : 307
Book Description
This contributed volume offers practical solutions and design-, modeling-, and implementation-related insights that address current research problems in memristors, memristive devices, and memristor computing. The book studies and addresses related challenges in and proposes solutions for the future of memristor computing. State-of-the-art research on memristor modeling, memristive interconnections, memory circuit architectures, software simulation tools, and applications of memristors in computing are presented. Utilising contributions from numerous experts in the field, written in clear language and illustrated throughout, this book is a comprehensive reference work. Memristor Computing Systems explains memristors and memristive devices in an accessible way for graduate students and researchers with a basic knowledge of electrical and control systems engineering, as well as prompting further research for more experienced academics.
Author: Publisher: BoD – Books on Demand ISBN: 1803561432 Category : Computers Languages : en Pages : 298
Book Description
Dive into the cutting-edge world of Neuromorphic Computing, a groundbreaking volume that unravels the secrets of brain-inspired computational paradigms. Spanning neuroscience, artificial intelligence, and hardware design, this book presents a comprehensive exploration of neuromorphic systems, empowering both experts and newcomers to embrace the limitless potential of brain-inspired computing. Discover the fundamental principles that underpin neural computation as we journey through the origins of neuromorphic architectures, meticulously crafted to mimic the brain’s intricate neural networks. Unlock the true essence of learning mechanisms – unsupervised, supervised, and reinforcement learning – and witness how these innovations are shaping the future of artificial intelligence.
Author: Harish Garg Publisher: Elsevier ISBN: 0443214824 Category : Computers Languages : en Pages : 289
Book Description
Primer to Neuromorphic Computing highlights critical and ongoing research into the diverse applications of neuromorphic computing. It includes an overview of primary scientific concepts for the research topic of neuromorphic computing, such as neurons as computational units, artificial intelligence, machine learning, and neuromorphic models. It also discusses the fundamental design method and organization of neuromorphic architecture. Hardware for neuromorphic systems can be developed by exploiting the magnetic properties of different materials. These systems are more energy efficient and enable faster computation . Magnetic tunnel junctions and magnetic textures can be employed to act as neurons and synapses. Neuromorphic systems have general intelligence like humans as they can apply knowledge gained in one domain to other domains. - Discusses potential neuromorphic applications in computing - Presents current trends and models in neuromorphic computing and neural network hardware architectures - Shows the development of novel devices and hardware to enable neuromorphic computing - Offers information about computation and learning principles for neuromorphic systems - Provides information about Neuromorphic implementations of neurobiological learning algorithms - Discusses biologically inspired neuromorphic systems and devices (including adaptive bio interfacing and hybrid systems consisting of living matter and synthetic matter)
Author: Abderazek Ben Abdallah Publisher: Springer Nature ISBN: 3030925250 Category : Computers Languages : en Pages : 260
Book Description
This book focuses on neuromorphic computing principles and organization and how to build fault-tolerant scalable hardware for large and medium scale spiking neural networks with learning capabilities. In addition, the book describes in a comprehensive way the organization and how to design a spike-based neuromorphic system to perform network of spiking neurons communication, computing, and adaptive learning for emerging AI applications. The book begins with an overview of neuromorphic computing systems and explores the fundamental concepts of artificial neural networks. Next, we discuss artificial neurons and how they have evolved in their representation of biological neuronal dynamics. Afterward, we discuss implementing these neural networks in neuron models, storage technologies, inter-neuron communication networks, learning, and various design approaches. Then, comes the fundamental design principle to build an efficient neuromorphic system in hardware. The challenges that need to be solved toward building a spiking neural network architecture with many synapses are discussed. Learning in neuromorphic computing systems and the major emerging memory technologies that promise neuromorphic computing are then given. A particular chapter of this book is dedicated to the circuits and architectures used for communication in neuromorphic systems. In particular, the Network-on-Chip fabric is introduced for receiving and transmitting spikes following the Address Event Representation (AER) protocol and the memory accessing method. In addition, the interconnect design principle is covered to help understand the overall concept of on-chip and off-chip communication. Advanced on-chip interconnect technologies, including si-photonic three-dimensional interconnects and fault-tolerant routing algorithms, are also given. The book also covers the main threats of reliability and discusses several recovery methods for multicore neuromorphic systems. This is important for reliable processing in several embedded neuromorphic applications. A reconfigurable design approach that supports multiple target applications via dynamic reconfigurability, network topology independence, and network expandability is also described in the subsequent chapters. The book ends with a case study about a real hardware-software design of a reliable three-dimensional digital neuromorphic processor geared explicitly toward the 3D-ICs biological brain’s three-dimensional structure. The platform enables high integration density and slight spike delay of spiking networks and features a scalable design. We present methods for fault detection and recovery in a neuromorphic system as well. Neuromorphic Computing Principles and Organization is an excellent resource for researchers, scientists, graduate students, and hardware-software engineers dealing with the ever-increasing demands on fault-tolerance, scalability, and low power consumption. It is also an excellent resource for teaching advanced undergraduate and graduate students about the fundamentals concepts, organization, and actual hardware-software design of reliable neuromorphic systems with learning and fault-tolerance capabilities.
Author: Khan, Muhammad Rahies Publisher: IGI Global ISBN: Category : Business & Economics Languages : en Pages : 511
Book Description
In the ever-increasing landscape of industry and technology, companies worldwide face an unprecedented challenge. The relentless march of progress, epitomized by the revolution of Industry 4.0, demands adaptation for survival and competitiveness. The integration of technologies such as the Internet of Things (IoT), blockchain, artificial intelligence, additive manufacturing, and robotics has irrevocably altered manufacturing and supply chain operations. What was initially a quest for augmented quality and production has now become an inexorable pursuit of sustainability. The United Nations Sustainable Development Goals (UNSDG) 2030 have left no room for exemptions, making sustainability an imperative at the heart of every business strategy. The answer to this pressing challenge lies within the pages of the book, Convergence of Industry 4.0 and Supply Chain Sustainability. It serves a meticulously curated collection of research that illuminates the intricacies of implementing Industry 4.0 and the ramifications for sustainable supply chains. Our work focuses on the associated challenges and opportunities encountered by the adoption of Industry 4.0 in supply chain management (SCM).
Author: Haijun Zhang Publisher: Springer Nature ISBN: 9811651884 Category : Computers Languages : en Pages : 774
Book Description
This book presents refereed proceedings of the Second International Conference Neural Computing for Advanced Applications, NCAA 2021, held in Guangzhou, China, in August, 2021. The 54 full papers papers were thorougly reviewed and selected from a total of 144 qualified submissions. The papers are organized in topical sections on neural network theory, cognitive sciences, neuro-system hardware implementations, and NN-based engineering applications; machine learning, data mining, data security and privacy protection, and data-driven applications; neural computing-based fault diagnosis, fault forecasting, prognostic management, and system modeling; computational intelligence, nature-inspired optimizers, and their engineering applications; fuzzy logic, neuro-fuzzy systems, decision making, and their applications in management sciences; control systems, network synchronization, system integration, and industrial artificial intelligence; computer vision, image processing, and their industrial applications; cloud/edge/fog computing, the Internet of Things/Vehicles(IoT/IoV), and their system optimization; spreading dynamics, forecasting, and other intelligent techniques against coronavirus disease (COVID-19).
Author: Monique Becker Publisher: IOS Press ISBN: 9789051991796 Category : Computers Languages : en Pages : 330
Book Description
The research reports presented in this volume focus on the implications of the T9000 microprocessor, which offers new elements in transputing and parallel programming. Subjects discussed include genetic algorithms, image analysis, neural networks, robotics and parallel architectures.
Author: Dhanasekar, S.
Author: Dhanasekar, S.
Author: Toshiyuki Yamane
Author: Ashish Kumar Luhach
Author: Leon O. Chua
Author: 
Author: Harish Garg
Author: Abderazek Ben Abdallah
Author: Khan, Muhammad Rahies
Author: Haijun Zhang
Author: Monique Becker