Stochastic Computing Techniques And Applications
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Stochastic Computing Techniques And Applications
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Author : Warren J. Gross
language : en
Publisher: Springer
Release Date : 2019-02-18
Stochastic Computing Techniques And Applications written by Warren J. Gross and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-02-18 with Technology & Engineering categories.
This book covers the history and recent developments of stochastic computing. Stochastic computing (SC) was first introduced in the 1960s for logic circuit design, but its origin can be traced back to von Neumann's work on probabilistic logic. In SC, real numbers are encoded by random binary bit streams, and information is carried on the statistics of the binary streams. SC offers advantages such as hardware simplicity and fault tolerance. Its promise in data processing has been shown in applications including neural computation, decoding of error-correcting codes, image processing, spectral transforms and reliability analysis. There are three main parts to this book. The first part, comprising Chapters 1 and 2, provides a history of the technical developments in stochastic computing and a tutorial overview of the field for both novice and seasoned stochastic computing researchers. In the second part, comprising Chapters 3 to 8, we review both well-established and emerging design approaches for stochastic computing systems, with a focus on accuracy, correlation, sequence generation, and synthesis. The last part, comprising Chapters 9 and 10, provides insights into applications in machine learning and error-control coding.
Stochastic Computing
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Author : Warren J. Gross
language : en
Publisher:
Release Date : 2019
Stochastic Computing written by Warren J. Gross and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019 with Probabilistic automata categories.
This book covers the history and recent developments of stochastic computing. Stochastic computing (SC) was first introduced in the 1960s for logic circuit design, but its origin can be traced back to von Neumann's work on probabilistic logic. In SC, real numbers are encoded by random binary bit streams, and information is carried on the statistics of the binary streams. SC offers advantages such as hardware simplicity and fault tolerance. Its promise in data processing has been shown in applications including neural computation, decoding of error-correcting codes, image processing, spectral transforms and reliability analysis. There are three main parts to this book. The first part, comprising Chapters 1 and 2, provides a history of the technical developments in stochastic computing and a tutorial overview of the field for both novice and seasoned stochastic computing researchers. In the second part, comprising Chapters 3 to 8, we review both well-established and emerging design approaches for stochastic computing systems, with a focus on accuracy, correlation, sequence generation, and synthesis. The last part, comprising Chapters 9 and 10, provides insights into applications in machine learning and error-control coding.
Stochastic Simulation Optimization An Optimal Computing Budget Allocation
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Author : Chun-hung Chen
language : en
Publisher: World Scientific
Release Date : 2010-06-04
Stochastic Simulation Optimization An Optimal Computing Budget Allocation written by Chun-hung Chen and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-06-04 with Computers categories.
With the advance of new computing technology, simulation is becoming very popular for designing large, complex and stochastic engineering systems, since closed-form analytical solutions generally do not exist for such problems. However, the added flexibility of simulation often creates models that are computationally intractable. Moreover, to obtain a sound statistical estimate at a specified level of confidence, a large number of simulation runs (or replications) is usually required for each design alternative. If the number of design alternatives is large, the total simulation cost can be very expensive.Stochastic Simulation Optimization addresses the pertinent efficiency issue via smart allocation of computing resource in the simulation experiments for optimization, and aims to provide academic researchers and industrial practitioners with a comprehensive coverage of OCBA approach for stochastic simulation optimization. Starting with an intuitive explanation of computing budget allocation and a discussion of its impact on optimization performance, a series of OCBA approaches developed for various problems are then presented, from the selection of the best design to optimization with multiple objectives. Finally, this book discusses the potential extension of OCBA notion to different applications such as data envelopment analysis, experiments of design and rare-event simulation.
Design And Applications Of Emerging Computer Systems
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Author : Weiqiang Liu
language : en
Publisher: Springer Nature
Release Date : 2024-01-13
Design And Applications Of Emerging Computer Systems written by Weiqiang Liu and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-01-13 with Technology & Engineering categories.
This book provides a single-source reference to the state-of-the-art in emerging computer systems. The authors address the technological contributions and developments at various hardware levels of new systems that compute under novel operational paradigms such as stochastic, probabilistic/inexact, neuromorphic, spintronic, bio-inspired and in-memory computing. Coverage includes the entire stack, i.e., from circuit, architecture, up to system level. This book includes tutorials, reviews and surveys of current theoretical/experimental results, design methodologies and a range of applications.
Approximate Computing Techniques
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Author : Alberto Bosio
language : en
Publisher: Springer Nature
Release Date : 2022-06-10
Approximate Computing Techniques written by Alberto Bosio and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-06-10 with Technology & Engineering categories.
This book serves as a single-source reference to the latest advances in Approximate Computing (AxC), a promising technique for increasing performance or reducing the cost and power consumption of a computing system. The authors discuss the different AxC design and validation techniques, and their integration. They also describe real AxC applications, spanning from mobile to high performance computing and also safety-critical applications.
Innovative Computing 2025 Volume 4
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Author : Hao-Shang Ma
language : en
Publisher: Springer Nature
Release Date : 2025-07-12
Innovative Computing 2025 Volume 4 written by Hao-Shang Ma and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-07-12 with Computers categories.
This book comprises select proceedings of the 7th International Conference on Innovative Computing which was held in Bangkok, Thailand, Jan 19-23, 2025 (IC 2025) focusing on cutting-edge research carried out in the areas of information technology, science, and engineering. Some of the themes covered in this book are cloud communications and networking, high performance computing, architecture for secure and interactive IoT, satellite communication, wearable network and system, infrastructure management, etc. The essays are written by leading international experts, making it a valuable resource for researchers and practicing engineers alike.
Modern Computational Techniques For Engineering Applications
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Author : Krishan Arora
language : en
Publisher: CRC Press
Release Date : 2023-07-21
Modern Computational Techniques For Engineering Applications written by Krishan Arora and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-07-21 with Computers categories.
Modern Computational Techniques for Engineering Applications presents recent computational techniques used in the advancement of modern grids with the integration of non-conventional energy sources like wind and solar energy. It covers data analytics tools for smart cities, smart towns, and smart computing for sustainable development. This book- Discusses the importance of renewable energy source applications wind turbines and solar panels for electrical grids. Presents optimization-based computing techniques like fuzzy logic, neural networks, and genetic algorithms that enhance the computational speed. Showcases cloud computing tools and methodologies such as cybersecurity testbeds and data security for better accuracy of data. Covers novel concepts on artificial neural networks, fuzzy systems, machine learning, and artificial intelligence techniques. Highlights application-based case studies including cloud computing, optimization methods, and the Industrial Internet of Things. The book comprehensively introduces modern computational techniques, starting from basic tools to highly advanced procedures, and their applications. It further highlights artificial neural networks, fuzzy systems, machine learning, and artificial intelligence techniques and how they form the basis for algorithms. It presents application-based case studies on cloud computing, optimization methods, blockchain technology, fog and edge computing, and the Industrial Internet of Things. It will be a valuable resource for senior undergraduates, graduate students, and academic researchers in diverse fields, including electrical engineering, electronics and communications engineering, and computer engineering.
Stochastic Global Optimization Methods And Applications To Chemical Biochemical Pharmaceutical And Environmental Processes
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Author : Ch. Venkateswarlu
language : en
Publisher: Elsevier
Release Date : 2019-11-18
Stochastic Global Optimization Methods And Applications To Chemical Biochemical Pharmaceutical And Environmental Processes written by Ch. Venkateswarlu and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-11-18 with Technology & Engineering categories.
Stochastic global optimization methods and applications to chemical, biochemical, pharmaceutical and environmental processes presents various algorithms that include the genetic algorithm, simulated annealing, differential evolution, ant colony optimization, tabu search, particle swarm optimization, artificial bee colony optimization, and cuckoo search algorithm. The design and analysis of these algorithms is studied by applying them to solve various base case and complex optimization problems concerning chemical, biochemical, pharmaceutical, and environmental engineering processes. Design and implementation of various classical and advanced optimization strategies to solve a wide variety of optimization problems makes this book beneficial to graduate students, researchers, and practicing engineers working in multiple domains. This book mainly focuses on stochastic, evolutionary, and artificial intelligence optimization algorithms with a special emphasis on their design, analysis, and implementation to solve complex optimization problems and includes a number of real applications concerning chemical, biochemical, pharmaceutical, and environmental engineering processes.
Stochastic Systems
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Author : Mircea Grigoriu
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-05-15
Stochastic Systems written by Mircea Grigoriu and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-05-15 with Technology & Engineering categories.
Uncertainty is an inherent feature of both properties of physical systems and the inputs to these systems that needs to be quantified for cost effective and reliable designs. The states of these systems satisfy equations with random entries, referred to as stochastic equations, so that they are random functions of time and/or space. The solution of stochastic equations poses notable technical difficulties that are frequently circumvented by heuristic assumptions at the expense of accuracy and rigor. The main objective of Stochastic Systems is to promoting the development of accurate and efficient methods for solving stochastic equations and to foster interactions between engineers, scientists, and mathematicians. To achieve these objectives Stochastic Systems presents: A clear and brief review of essential concepts on probability theory, random functions, stochastic calculus, Monte Carlo simulation, and functional analysis Probabilistic models for random variables and functions needed to formulate stochastic equations describing realistic problems in engineering and applied sciences Practical methods for quantifying the uncertain parameters in the definition of stochastic equations, solving approximately these equations, and assessing the accuracy of approximate solutions Stochastic Systems provides key information for researchers, graduate students, and engineers who are interested in the formulation and solution of stochastic problems encountered in a broad range of disciplines. Numerous examples are used to clarify and illustrate theoretical concepts and methods for solving stochastic equations. The extensive bibliography and index at the end of the book constitute an ideal resource for both theoreticians and practitioners.
Introduction To Stochastic Programming
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Author : John R. Birge
language : en
Publisher: Springer Science & Business Media
Release Date : 2006-04-06
Introduction To Stochastic Programming written by John R. Birge and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006-04-06 with Mathematics categories.
This rapidly developing field encompasses many disciplines including operations research, mathematics, and probability. Conversely, it is being applied in a wide variety of subjects ranging from agriculture to financial planning and from industrial engineering to computer networks. This textbook provides a first course in stochastic programming suitable for students with a basic knowledge of linear programming, elementary analysis, and probability. The authors present a broad overview of the main themes and methods of the subject, thus helping students develop an intuition for how to model uncertainty into mathematical problems, what uncertainty changes bring to the decision process, and what techniques help to manage uncertainty in solving the problems. The early chapters introduce some worked examples of stochastic programming, demonstrate how a stochastic model is formally built, develop the properties of stochastic programs and the basic solution techniques used to solve them. The book then goes on to cover approximation and sampling techniques and is rounded off by an in-depth case study. A well-paced and wide-ranging introduction to this subject.