Signals, Instrumentation, Control, And Machine Learning: An Integrative Introduction, Joseph Bentsman
Автор: Anand, R. Название: Digital signal processing ISBN: 1683928024 ISBN-13(EAN): 9781683928027 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 8959.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Designed to cover the fundamental concepts of digital signal processing, this book introduces topics such as discrete-time signals, the z-transform, frequency analysis, discrete and fast Fourier transforms, digital filters, FIR, statistical DSP, applications, and more.
Автор: Franco Davoli; Norbert Meyer; Roberto Pugliese; Sa Название: Grid Enabled Remote Instrumentation ISBN: 1441935061 ISBN-13(EAN): 9781441935069 Издательство: Springer Рейтинг: Цена: 32651.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Grid architectures, which are viewed as tools for the integration of distributed resources, play a significant role as managers of computational resources. This book focuses on a number of aspects related to the effective exploitation of remote instrumentation on the grid.
Описание: This book is devoted to the investigation of the main issues related to the sustainable realization of tele-laboratories, where real and virtual instrumentation can be shared and used in a collaborative environment.
Описание: Signal Processing is one of themost importantspecializations in engineering, and computer sciences. It derives input from physics, mathematics and is an indispensable feature of all natural- and life sciences in research and in application. The new s
Описание: THE SERIES: ADVANCES IN SYSTEMS, SIGNALS AND DEVICES Systems, Signals & Devices is one of the large specializations in electrical engineering, mechanical engineering and computer sciences. It derives input from physics, mathematics and is an indispensable feature of all natural- and life sciences in research and in application. The new series “Advances in Systems, Signals and Devices” presents original publications mainly from speakers on the International Multi-Conference on Systems, Signal and Devices but also from other international authors. The Conference is a forum for researchers and specialists in different fi elds covering all types of sensors and measurement systems.
Автор: Masashi Sugiyama Название: Introduction to Statistical Machine Learning ISBN: 0128021217 ISBN-13(EAN): 9780128021217 Издательство: Elsevier Science Рейтинг: Цена: 17180.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
Machine learning allows computers to learn and discern patterns without actually being programmed. When Statistical techniques and machine learning are combined together they are a powerful tool for analysing various kinds of data in many computer science/engineering areas including, image processing, speech processing, natural language processing, robot control, as well as in fundamental sciences such as biology, medicine, astronomy, physics, and materials.
Introduction to Statistical Machine Learning provides ageneral introduction to machine learning that covers a wide range of topics concisely and will help you bridge the gap between theory and practice. Part I discusses the fundamental concepts of statistics and probability that are used in describing machine learning algorithms. Part II and Part III explain the two major approaches of machine learning techniques; generative methods and discriminative methods. While Part III provides an in-depth look at advanced topics that play essential roles in making machine learning algorithms more useful in practice. The accompanying MATLAB/Octave programs provide you with the necessary practical skills needed to accomplish a wide range of data analysis tasks.
Provides the necessary background material to understand machine learning such as statistics, probability, linear algebra, and calculus
Complete coverage of the generative approach to statistical pattern recognition and the discriminative approach to statistical machine learning
Includes MATLAB/Octave programs so that readers can test the algorithms numerically and acquire both mathematical and practical skills in a wide range of data analysis tasks
Discusses a wide range of applications in machine learning and statistics and provides examples drawn from image processing, speech processing, natural language processing, robot control, as well as biology, medicine, astronomy, physics, and materials
Автор: Wang Название: Introduction to Transfer Learning ISBN: 9811975833 ISBN-13(EAN): 9789811975837 Издательство: Springer Рейтинг: Цена: 6986.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Transfer learning is one of the most important technologies in the era of artificial intelligence and deep learning. It seeks to leverage existing knowledge by transferring it to another, new domain. Over the years, a number of relevant topics have attracted the interest of the research and application community: transfer learning, pre-training and fine-tuning, domain adaptation, domain generalization, and meta-learning. This book offers a comprehensive tutorial on an overview of transfer learning, introducing new researchers in this area to both classic and more recent algorithms. Most importantly, it takes a “student’s” perspective to introduce all the concepts, theories, algorithms, and applications, allowing readers to quickly and easily enter this area. Accompanying the book, detailed code implementations are provided to better illustrate the core ideas of several important algorithms, presenting good examples for practice.
Автор: Wayne Stark Название: Introduction to Digital Communications ISBN: 1009220810 ISBN-13(EAN): 9781009220811 Издательство: Cambridge Academ Рейтинг: Цена: 12355.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Master the fundamentals of digital communications systems with this accessible and hands-on introductory textbook, carefully interweaving theory and practice. The just-in-time approach introduces essential background as needed, keeping academic theory firmly linked to practical applications. The example-led teaching frames key concepts in the context of real-world systems, such as 5G, WiFi, and GPS. Stark provides foundational material on the trade-offs between energy and bandwidth efficiency, giving students a solid grounding in the fundamental challenges of designing digital communications systems. Features include over 300 illustrative figures, 80 examples, and 130 end-of-chapter problems to reinforce student understanding, with solutions for instructors. Accompanied online by lecture slides, computational MATLAB® and Python resources, and supporting data sets, this is the ideal introduction to digital communications for senior undergraduate and graduate students in electrical engineering.
Автор: Chirag Shah Название: A Hands-On Introduction to Machine Learning ISBN: 1009123300 ISBN-13(EAN): 9781009123303 Издательство: Cambridge Academ Рейтинг: Цена: 7762.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Packed with real-world examples, industry insights and practical activities, this textbook is designed to teach machine learning in a way that is easy to understand and apply. It assumes only a basic knowledge of technology, making it an ideal resource for students and professionals, including those who are new to computer science.
Автор: Sutton, Richard S. Barto, Andrew G. Название: Reinforcement learning ISBN: 0262193981 ISBN-13(EAN): 9780262193986 Издательство: MIT Press Рейтинг: Цена: 10040.00 р. Наличие на складе: Нет в наличии.
Описание: An account of key ideas and algorithms in reinforcement learning. The discussion ranges from the history of the field`s intellectual foundations to recent developments and applications. Areas studied include reinforcement learning problems in terms of Markov decision problems and solution methods.
Автор: William W. Hsieh Название: Introduction to Environmental Data Science ISBN: 1107065550 ISBN-13(EAN): 9781107065550 Издательство: Cambridge Academ Рейтинг: Цена: 9821.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Statistical and machine learning methods have many applications in the environmental sciences, including prediction and data analysis in meteorology, hydrology and oceanography; pattern recognition for satellite images from remote sensing; management of agriculture and forests; assessment of climate change; and much more. With rapid advances in machine learning in the last decade, this book provides an urgently needed, comprehensive guide to machine learning and statistics for students and researchers interested in environmental data science. It includes intuitive explanations covering the relevant background mathematics, with examples drawn from the environmental sciences. A broad range of topics is covered, including correlation, regression, classification, clustering, neural networks, random forests, boosting, kernel methods, evolutionary algorithms and deep learning, as well as the recent merging of machine learning and physics. End?of?chapter exercises allow readers to develop their problem-solving skills, and online datasets allow readers to practise analysis of real data.
Автор: Nagahara Masaaki Название: Sparsity Methods for Systems and Control ISBN: 1680837249 ISBN-13(EAN): 9781680837247 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 12335.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Offers a comprehensive guide to sparsity methods for systems and control, from standard sparsity methods in finite-dimensional vector spaces to optimal control methods in infinite-dimensional function spaces.The primary objective of this book is to show how to use sparsity methods for several engineering problems.
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