Author : Huanglong Li
Publisher : Frontiers Media SA
Page : 203 pages
File Size : 16,51 MB
Release : 2022-02-21
Category : Science
ISBN : 2889744604
Author : Julien Clinton Sprott
Publisher : World Scientific
Page : 357 pages
File Size : 22,43 MB
Release : 2021-12-17
Category : Science
ISBN : 9811240019
Chaos is the study of the underlying determinism in the seemingly random phenomena that occur all around us. One of the best experimental demonstrations of chaos occurs in electrical circuits when the parameters are chosen carefully. We will show you how to construct such chaotic circuits for use in your own studies and demonstrations while teaching you the basics of chaos.This book should be of interest to researchers and hobbyists looking for a simple way to produce a chaotic signal. It should also be useful to students and their instructors as an engaging way to learn about chaotic dynamics and electronic circuits. The book assumes only an elementary knowledge of calculus and the ability to understand a schematic diagram and the components that it contains.You will get the most out of this book if you can construct the circuits for yourself. There is no substitute for the thrill and insight of seeing the output of a circuit you built unfold as the trajectory wanders in real time across your oscilloscope screen. A goal of this book is to inspire and delight as well as to teach.
Author : Anuradha D. Thakare
Publisher : John Wiley & Sons
Page : 245 pages
File Size : 13,12 MB
Release : 2023-03-21
Category : Computers
ISBN : 1119857295
ARTIFICIAL INTELLIGENCE APPLICATIONS and RECONFIGURABLE ARCHITECTURES The primary goal of this book is to present the design, implementation, and performance issues of AI applications and the suitability of the FPGA platform. This book covers the features of modern Field Programmable Gate Arrays (FPGA) devices, design techniques, and successful implementations pertaining to AI applications. It describes various hardware options available for AI applications, key advantages of FPGAs, and contemporary FPGA ICs with software support. The focus is on exploiting parallelism offered by FPGA to meet heavy computation requirements of AI as complete hardware implementation or customized hardware accelerators. This is a comprehensive textbook on the subject covering a broad array of topics like technological platforms for the implementation of AI, capabilities of FPGA, suppliers’ software tools and hardware boards, and discussion of implementations done by researchers to encourage the AI community to use and experiment with FPGA. Readers will benefit from reading this book because It serves all levels of students and researcher’s as it deals with the basics and minute details of Ecosystem Development Requirements for Intelligent applications with reconfigurable architectures whereas current competitors’ books are more suitable for understanding only reconfigurable architectures. It focuses on all aspects of machine learning accelerators for the design and development of intelligent applications and not on a single perspective such as only on reconfigurable architectures for IoT applications. It is the best solution for researchers to understand how to design and develop various AI, deep learning, and machine learning applications on the FPGA platform. It is the best solution for all types of learners to get complete knowledge of why reconfigurable architectures are important for implementing AI-ML applications with heavy computations. Audience Researchers, industrial experts, scientists, and postgraduate students who are working in the fields of computer engineering, electronics, and electrical engineering, especially those specializing in VLSI and embedded systems, FPGA, artificial intelligence, Internet of Things, and related multidisciplinary projects.
Author : Calin Ciufudean
Publisher : BoD – Books on Demand
Page : 126 pages
File Size : 13,20 MB
Release : 2018-10-03
Category : Mathematics
ISBN : 1789841151
Nowadays, scientific research deals with alternative solutions for creating non-traditional computing systems, such as neural network architectures where the stochastic nature and live dynamics of memristive models play a key role. The features of memristors make it possible to direct processing and analysis of both biosystems and systems driven by artificial intelligence, as well as develop plausible physical models of spiking neural networks with self-organization. This book deals with advanced applications illustrating these concepts, and delivers an important contribution for the achievement of the next generation of intelligent hybrid biostructures. Different modeling and simulation tools can deliver an alternative to funding the theoretical approach as well as practical implementation of memristive systems.
Author : Jordi Suñé
Publisher : MDPI
Page : 244 pages
File Size : 12,46 MB
Release : 2020-04-09
Category : Technology & Engineering
ISBN : 3039285769
Artificial Intelligence (AI) has found many applications in the past decade due to the ever increasing computing power. Artificial Neural Networks are inspired in the brain structure and consist in the interconnection of artificial neurons through artificial synapses. Training these systems requires huge amounts of data and, after the network is trained, it can recognize unforeseen data and provide useful information. The so-called Spiking Neural Networks behave similarly to how the brain functions and are very energy efficient. Up to this moment, both spiking and conventional neural networks have been implemented in software programs running on conventional computing units. However, this approach requires high computing power, a large physical space and is energy inefficient. Thus, there is an increasing interest in developing AI tools directly implemented in hardware. The first hardware demonstrations have been based on CMOS circuits for neurons and specific communication protocols for synapses. However, to further increase training speed and energy efficiency while decreasing system size, the combination of CMOS neurons with memristor synapses is being explored. The memristor is a resistor with memory which behaves similarly to biological synapses. This book explores the state-of-the-art of neuromorphic circuits implementing neural networks with memristors for AI applications.
Author : Balwinder Raj
Publisher : Elsevier
Page : 254 pages
File Size : 35,1 MB
Release : 2023-11-08
Category : Technology & Engineering
ISBN : 0323998119
Nanoscale Memristor Device and Circuits Design provides theoretical frameworks, including (i) the background of memristors, (ii) physics of memristor and their modeling, (iii) menristive device applications, and (iv) circuit design for security and authentication. The book focuses on a broad aspect of realization of these applications as low cost and reliable devices. This is an important reference that will help materials scientists and engineers understand the production and applications of nanoscale memrister devices. A memristor is a two-terminal memory nanoscale device that stores information in terms of high/low resistance. It can retain information even when the power source is removed, i.e., "non-volatile." In contrast to MOS Transistors (MOST), which are the building blocks of all modern mobile and computing devices, memristors are relatively immune to radiation, as well as parasitic effects, such as capacitance, and can be much more reliable. This is extremely attractive for critical safety applications, such as nuclear and aerospace, where radiation can cause failure in MOST-based systems. - Outlines the major principles of circuit design for nanoelectronic applications - Explores major applications, including memristor-based memories, sensors, solar cells, or memristor-based hardware and software security applications - Assesses the major challenges to manufacturing nanoscale memristor devices at an industrial scale
Author : Yao-Feng Chang
Publisher : BoD – Books on Demand
Page : 204 pages
File Size : 22,70 MB
Release : 2024-06-12
Category : Technology & Engineering
ISBN : 0854661670
This book presents excellent comprehensive and interdisciplinary research on memristor devices and their corresponding applications. The authors discuss a wide range of topics, including material and physical modeling, materials physics and analytics, devices in miniature scale, advanced functional circuits, high-speed computing systems and integration for logic applications, other novel emerging device concepts and circuit schemes, and much more.
Author : Sundarapandian Vaidyanathan
Publisher : Springer
Page : 513 pages
File Size : 26,90 MB
Release : 2017-02-15
Category : Technology & Engineering
ISBN : 3319517244
This book reports on the latest advances in and applications of memristors, memristive devices and systems. It gathers 20 contributed chapters by subject experts, including pioneers in the field such as Leon Chua (UC Berkeley, USA) and R.S. Williams (HP Labs, USA), who are specialized in the various topics addressed in this book, and covers broad areas of memristors and memristive devices such as: memristor emulators, oscillators, chaotic and hyperchaotic memristive systems, control of memristive systems, memristor-based min-max circuits, canonic memristors, memristive-based neuromorphic applications, implementation of memristor-based chaotic oscillators, inverse memristors, linear memristor devices, delayed memristive systems, flux-controlled memristive emulators, etc. Throughout the book, special emphasis is given to papers offering practical solutions and design, modeling, and implementation insights to address current research problems in memristors, memristive devices and systems. As such, it offers a valuable reference book on memristors and memristive devices for graduate students and researchers with a basic knowledge of electrical and control systems engineering.
Author : Andrew Adamatzky
Publisher : Springer Science & Business Media
Page : 716 pages
File Size : 32,68 MB
Release : 2013-12-18
Category : Computers
ISBN : 3319026305
Using memristors one can achieve circuit functionalities that are not possible to establish with resistors, capacitors and inductors, therefore the memristor is of great pragmatic usefulness. Potential unique applications of memristors are in spintronic devices, ultra-dense information storage, neuromorphic circuits and programmable electronics. Memristor Networks focuses on the design, fabrication, modelling of and implementation of computation in spatially extended discrete media with many memristors. Top experts in computer science, mathematics, electronics, physics and computer engineering present foundations of the memristor theory and applications, demonstrate how to design neuromorphic network architectures based on memristor assembles, analyse varieties of the dynamic behaviour of memristive networks and show how to realise computing devices from memristors. All aspects of memristor networks are presented in detail, in a fully accessible style. An indispensable source of information and an inspiring reference text, Memristor Networks is an invaluable resource for future generations of computer scientists, mathematicians, physicists and engineers.
Author : Fernando Corinto
Publisher : Springer Nature
Page : 438 pages
File Size : 15,47 MB
Release : 2020-10-31
Category : Technology & Engineering
ISBN : 3030556514
This book presents a new approach to the study of physical nonlinear circuits and advanced computing architectures with memristor devices. Such a unified approach to memristor theory has never been systematically presented in book form. After giving an introduction on memristor-based nonlinear dynamical circuits (e.g., periodic/chaotic oscillators) and their use as basic computing analogue elements, the authors delve into the nonlinear dynamical properties of circuits and systems with memristors and present the flux-charge analysis, a novel method for analyzing the nonlinear dynamics starting from writing Kirchhoff laws and constitutive relations of memristor circuit elements in the flux-charge domain. This analysis method reveals new peculiar and intriguing nonlinear phenomena in memristor circuits, such as the coexistence of different nonlinear dynamical behaviors, extreme multistability and bifurcations without parameters. The book also describes how arrays of memristor-based nonlinear oscillators and locally-coupled neural networks can be applied in the field of analog computing architectures, for example for pattern recognition. The book will be of interest to scientists and engineers involved in the conceptual design of physical memristor devices and systems, mathematical and circuit models of physical processes, circuits and networks design, system engineering, or data processing and system analysis.
