The Momentum Method
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Essentials Of Generative Ai
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Author : Takeshi Okadome
language : en
Publisher: Springer Nature
Release Date : 2025-02-01
Essentials Of Generative Ai written by Takeshi Okadome and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-02-01 with Computers categories.
This book provides a concise yet comprehensive introduction to generative artificial intelligence. The first part explains the foundational technologies and architectures that support the realization of generative models. It covers evolved and deepened elements, word embeddings as a representative example of representation learning, and the Transformer as a network foundation, along with its underlying attention mechanism. Reinforcement learning, which became essential for elevating large-scale language models to language generation models, is also discussed in detail, focusing on essential aspects. The second part deals with language generation. It starts by elucidating language models and introduces large-scale language models with broad applications as the foundational architecture of language processing, further discussing language generation models as their evolution. Though not common terminology, in this book, models such as ChatGPT and Llama 2, which are large-scale language models fine-tuned using reinforcement learning, are referred to as generative language models. The third part addresses image generation, discussing variational autoencoders and the remarkable diffusion models. Additionally, it explains Generative Adversarial Networks(GAN). Although GAN poses challenges due to unstable learning, their conceptual framework is widely applicable, especially Wasserstein GAN seems suitable for introducing optimal trans- port distance, which is utilized in various scenarios. This book primarily serves as a companion for researchers or graduate students in machine learning, aiming to help them understand the essence of generative AI and lay the groundwork for advancing their own research.
Learning In Energy Efficient Neuromorphic Computing Algorithm And Architecture Co Design
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Author : Nan Zheng
language : en
Publisher: John Wiley & Sons
Release Date : 2019-10-18
Learning In Energy Efficient Neuromorphic Computing Algorithm And Architecture Co Design written by Nan Zheng and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-10-18 with Computers categories.
Explains current co-design and co-optimization methodologies for building hardware neural networks and algorithms for machine learning applications This book focuses on how to build energy-efficient hardware for neural networks with learning capabilities—and provides co-design and co-optimization methodologies for building hardware neural networks that can learn. Presenting a complete picture from high-level algorithm to low-level implementation details, Learning in Energy-Efficient Neuromorphic Computing: Algorithm and Architecture Co-Design also covers many fundamentals and essentials in neural networks (e.g., deep learning), as well as hardware implementation of neural networks. The book begins with an overview of neural networks. It then discusses algorithms for utilizing and training rate-based artificial neural networks. Next comes an introduction to various options for executing neural networks, ranging from general-purpose processors to specialized hardware, from digital accelerator to analog accelerator. A design example on building energy-efficient accelerator for adaptive dynamic programming with neural networks is also presented. An examination of fundamental concepts and popular learning algorithms for spiking neural networks follows that, along with a look at the hardware for spiking neural networks. Then comes a chapter offering readers three design examples (two of which are based on conventional CMOS, and one on emerging nanotechnology) to implement the learning algorithm found in the previous chapter. The book concludes with an outlook on the future of neural network hardware. Includes cross-layer survey of hardware accelerators for neuromorphic algorithms Covers the co-design of architecture and algorithms with emerging devices for much-improved computing efficiency Focuses on the co-design of algorithms and hardware, which is especially critical for using emerging devices, such as traditional memristors or diffusive memristors, for neuromorphic computing Learning in Energy-Efficient Neuromorphic Computing: Algorithm and Architecture Co-Design is an ideal resource for researchers, scientists, software engineers, and hardware engineers dealing with the ever-increasing requirement on power consumption and response time. It is also excellent for teaching and training undergraduate and graduate students about the latest generation neural networks with powerful learning capabilities.
Technical Note National Advisory Committee For Aeronautics
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Author : United States. National Advisory Committee for Aeronautics
language : en
Publisher:
Release Date : 1951
Technical Note National Advisory Committee For Aeronautics written by United States. National Advisory Committee for Aeronautics and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1951 with Aeronautics categories.
Axially Symmetric Shapes With Minimum Wave Drag
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Author : Maxwell Alfred Heaslet
language : en
Publisher:
Release Date : 1955
Axially Symmetric Shapes With Minimum Wave Drag written by Maxwell Alfred Heaslet and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1955 with Aeronautics categories.
The external wave drag of bodies of revolution moving at supersonic speeds can be expressed either in terms of the geometry of the body, or in terms of the body-simulating axial source distribution. For purposes of deriving optimum bodies under various given condtions, it is found that the second of the methods mentioned is the more tractable. By use of a quasi-cylindrical theory, that is, the boundary conditions are applied on the surface of a cylinder rather than on the body itself, the variational problems of the optimum bodies having prescribed volume or caliber are solved. The streamwise variations of cross-section area and drags of the bodies are exhibited, and some numerical results are given. The solutions are found to depend upon a single parameter involving Mach number and radius-lenght ration of the given cylinder. Variation of this parameter from zero to infinity gives the spectrum of optimum bodies with the given condition from the slender-body result of the two-dimensional. The numerical results show that for increasing values of the parameter, the optimum shapes quickly approach the two-dimensional.
Artificial Intelligence Based Electrical Machines And Drives
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Author : Peter Vas
language : en
Publisher: Oxford University Press
Release Date : 1999-01-28
Artificial Intelligence Based Electrical Machines And Drives written by Peter Vas and has been published by Oxford University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 1999-01-28 with Computers categories.
Recently, AI techniques have received increased attention world-wide and at present 2 industrial drives incorporate some form of AI. This is the first comprehensive book which discusses numerous AI applications to electrical machines and drives.
Noise Research In Semiconductor Physics
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Author : N Lukyanchikova
language : en
Publisher: CRC Press
Release Date : 2020-08-18
Noise Research In Semiconductor Physics written by N Lukyanchikova and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-08-18 with Technology & Engineering categories.
This book demonstrates the role and abilities of fluctuation in semiconductor physics, and shows what kinds of physical information are involved in the noise characteristics of semiconductor materials and devices, how this information may be decoded and which advantages are inherent to the noise methods. The text provides a comprehensive account of current results, addressing problems which have not previously been covered in Western literature, including the excess noise of tunnel-recombination currents and photocurrents in diodes, fluctuation phenomena in a real photoconductor with different recombination centers, and methods of noise spectroscopy of levels in a wide range of materials and devices.
Vehicle Accident Analysis And Reconstruction Methods
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Author : Matthew Brach
language : en
Publisher: SAE International
Release Date : 2022-01-07
Vehicle Accident Analysis And Reconstruction Methods written by Matthew Brach and has been published by SAE International this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-01-07 with Technology & Engineering categories.
In this third edition of Vehicle Accident Analysis & Reconstruction Methods, Raymond M. Brach and R. Matthew Brach have expanded and updated their essential work for professionals in the field of accident reconstruction. Most accidents can be reconstructed effectively using of calculations and investigative and experimental data: the authors present the latest scientific, engineering, and mathematical reconstruction methods, providing a firm scientific foundation for practitioners. Accidents that cannot be reconstructed using the methods in this book are rare. In recent decades, the field of crash reconstruction has been transformed through the use of technology. The advent of event data records (EDRs) on vehicles signaled the era of modern crash reconstruction, which utilizes the same physical evidence that was previously available as well as electronic data that are measured/captured before, during, and after the collision. There is increased demand for more professional and accurate reconstruction as more crash data is available from vehicle sensors. The third edition of this essential work includes a new chapter on the use of EDRs as well as examples using EDR data in accident reconstruction. Early chapters feature foundational material that is necessary for the understanding of vehicle collisions and vehicle motion; later chapters present applications of the methods and include example reconstructions. As a result, Vehicle Accident Analysis & Reconstruction Methods remains the definitive resource in accident reconstruction.
Nature Inspired Optimization Techniques For Image Processing Applications
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Author : Jude Hemanth
language : en
Publisher: Springer
Release Date : 2018-09-19
Nature Inspired Optimization Techniques For Image Processing Applications written by Jude Hemanth and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-09-19 with Technology & Engineering categories.
This book provides a platform for exploring nature-inspired optimization techniques in the context of imaging applications. Optimization has become part and parcel of all computational vision applications, and since the amount of data used in these applications is vast, the need for optimization techniques has increased exponentially. These accuracy and complexity are a major area of concern when it comes to practical applications. However, these optimization techniques have not yet been fully explored in the context of imaging applications. By presenting interdisciplinary concepts, ranging from optimization to image processing, the book appeals to a broad readership, while also encouraging budding engineers to pursue and employ innovative nature-inspired techniques for image processing applications.
Anomaly Detection In Video Surveillance
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Author : Xiaochun Wang
language : en
Publisher: Springer Nature
Release Date : 2024-08-06
Anomaly Detection In Video Surveillance written by Xiaochun Wang and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-08-06 with Computers categories.
Anomaly detection in video surveillance stands at the core of numerous real-world applications that have broad impact and generate significant academic and industrial value. The key advantage of writing the book at this point in time is that the vast amount of work done by computer scientists over the last few decades has remained largely untouched by a formal book on the subject, although these techniques significantly advance existing methods of image and video analysis and understanding by taking advantage of anomaly detection in the data mining community and visual analysis in the computer vision community. The proposed book provides a comprehensive coverage of the advances in video based anomaly detection, including topics such as the theories of anomaly detection and machine perception for the functional analysis of abnormal events in general, the identification of abnormal behaviour and crowd abnormal behaviour in particular, the current understanding of computer vision development, and the application of this present understanding towards improving video-based anomaly detection in theory and coding with OpenCV. The book also provides a perspective on deep learning on human action recognition and behaviour analysis, laying the groundwork for future advances in these areas. Overall, the chapters of this book have been carefully organized with extensive bibliographic notes attached to each chapter. One of the goals is to provide the first systematic and comprehensive description of the range of data-driven solutions currently being developed up to date for such purposes. Another is to serve a dual purpose so that students and practitioners can use it as a textbook while researchers can use it as a reference book. A final goal is to provide a comprehensive exposition of the topic of anomaly detection in video media from multiple points of view.
Mathematical Theories Of Machine Learning Theory And Applications
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Author : Bin Shi
language : en
Publisher: Springer
Release Date : 2019-06-12
Mathematical Theories Of Machine Learning Theory And Applications written by Bin Shi and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-06-12 with Technology & Engineering categories.
This book studies mathematical theories of machine learning. The first part of the book explores the optimality and adaptivity of choosing step sizes of gradient descent for escaping strict saddle points in non-convex optimization problems. In the second part, the authors propose algorithms to find local minima in nonconvex optimization and to obtain global minima in some degree from the Newton Second Law without friction. In the third part, the authors study the problem of subspace clustering with noisy and missing data, which is a problem well-motivated by practical applications data subject to stochastic Gaussian noise and/or incomplete data with uniformly missing entries. In the last part, the authors introduce an novel VAR model with Elastic-Net regularization and its equivalent Bayesian model allowing for both a stable sparsity and a group selection.