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Dan Simon Optimal State Estimation

Купить за 14501.6 RUR

A bottom-up approach that enables readers to master and apply the latest techniques in state estimation This book offers the best mathematical approaches to estimating the state of a general system. The author presents state estimation theory clearly and rigorously, providing the right amount of
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Bangjun Lei Classification, Parameter Estimation and State Estimation

Купить за 11240.41 RUR

A practical introduction to intelligent computer vision theory, design, implementation, and technology The past decade has witnessed epic growth in image processing and intelligent computer vision technology. Advancements in machine learning methods—especially among adaboost varieties and particle
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David Tax M.J. Classification, Parameter Estimation and State Estimation

Купить за 15110.99 RUR

Classification, Parameter Estimation and State Estimation is a practical guide for data analysts and designers of measurement systems and postgraduates students that are interested in advanced measurement systems using MATLAB. 'Prtools' is a powerful MATLAB toolbox for pattern recognition and is
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Simon Sheather J. Robust Estimation and Testing

Купить за 25862.73 RUR

An introduction to the theory and methods of robust statistics, providing students with practical methods for carrying out robust procedures in a variety of statistical contexts and explaining the advantages of these procedures. In addition, the text develops techniques and concepts likely to be
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Mohamed Najim Modeling, Estimation and Optimal Filtration in Signal Processing

Купить за 22629.89 RUR

The purpose of this book is to provide graduate students and practitioners with traditional methods and more recent results for model-based approaches in signal processing. Firstly, discrete-time linear models such as AR, MA and ARMA models, their properties and their limitations are introduced. In
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Dan Simon Evolutionary Optimization Algorithms

Купить за 12907.92 RUR

A clear and lucid bottom-up approach to the basic principles of evolutionary algorithms Evolutionary algorithms (EAs) are a type of artificial intelligence. EAs are motivated by optimization processes that we observe in nature, such as natural selection, species migration, bird swarms, human
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Группа авторов Advances in Electric Power and Energy

Купить за 12929.32 RUR

A guide to the role of static state estimation in the mitigation of potential system failures With contributions from a noted panel of experts on the topic, Advances in Electric Power and Energy: Static State Estimation addresses the wide-range of issues concerning static state estimation as a
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Yaakov Bar-Shalom Estimation with Applications to Tracking and Navigation

Купить за 15610 RUR

Expert coverage of the design and implementation of state estimation algorithms for tracking and navigation Estimation with Applications to Tracking and Navigation treats the estimation of various quantities from inherently inaccurate remote observations. It explains state estimator design using a
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Evgeniy Belilovsky Happiness instead of capital and spirituality. Model of an Optimal State

Купить за 120 RUR

Dr. Evgeniy Belilovsky – In Soviet times, leading legal journals published his papers which presented an alternative to the subsequent development of the USSR: the 1982 article, describing the proposed mechanism for fighting corruption and the 1985 review describing the proposed socio-economic
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Gerhard Schmidt Acoustic Echo and Noise Control

Купить за 14944.63 RUR

Authors are well known and highly recognized by the «acoustic echo and noise community.» Presents a detailed description of practical methods to control echo and noise Develops a statistical theory for optimal control parameters and presents practical estimation and approximation methods
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Didier Dumur Zonotopes

Купить за 15503.63 RUR

This title focuses on two significant problems in the field of automatic control, in particular state estimation and robust Model Predictive Control under input and state constraints, bounded disturbances and measurement noises. The authors build upon previous results concerning zonotopic
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