Автор: Train Kenneth E Название: Discrete Choice Methods with Simulation ISBN: 0521747384 ISBN-13(EAN): 9780521747387 Издательство: Cambridge Academ Рейтинг: Цена: 49630.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book describes the new generation of discrete choice methods, focusing on the many advances that are made possible by simulation. Each of the major models is covered including logit, generalized extreme value, or GEV, probit, and mixed logit, plus a variety of specifications that build on these basics.
Автор: Guerrero, Hector Название: Excel data analysis ISBN: 3030012786 ISBN-13(EAN): 9783030012786 Издательство: Springer Рейтинг: Цена: 93160.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book offers a comprehensive and readable introduction to modern business and data analytics.
Автор: Rakhee Kulshrestha Название: Mathematical modeling and computation of real-time problems ISBN: 0367517434 ISBN-13(EAN): 9780367517434 Издательство: Taylor&Francis Рейтинг: Цена: 163330.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book covers an interdisciplinary approach for understanding mathematical modeling by offering a collection of models, solved problems related to the models the methodologies employed, and the results using projects and case studies with insight into the operation of substantial real-time systems.
Автор: Ozaki Tohru Название: Time Series Modeling of Neuroscience Data ISBN: 1420094602 ISBN-13(EAN): 9781420094602 Издательство: Taylor&Francis Рейтинг: Цена: 163330.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание:
Recent advances in brain science measurement technology have given researchers access to very large-scale time series data such as EEG/MEG data (20 to 100 dimensional) and fMRI (140,000 dimensional) data. To analyze such massive data, efficient computational and statistical methods are required.
Time Series Modeling of Neuroscience Data shows how to efficiently analyze neuroscience data by the Wiener-Kalman-Akaike approach, in which dynamic models of all kinds, such as linear/nonlinear differential equation models and time series models, are used for whitening the temporally dependent time series in the framework of linear/nonlinear state space models. Using as little mathematics as possible, this book explores some of its basic concepts and their derivatives as useful tools for time series analysis. Unique features include:
A statistical identification method of highly nonlinear dynamical systems such as the Hodgkin-Huxley model, Lorenz chaos model, Zetterberg Model, and more
Methods and applications for Dynamic Causality Analysis developed by Wiener, Granger, and Akaike
A state space modeling method for dynamicization of solutions for the Inverse Problems
A heteroscedastic state space modeling method for dynamic non-stationary signal decomposition for applications to signal detection problems in EEG data analysis
An innovation-based method for the characterization of nonlinear and/or non-Gaussian time series
An innovation-based method for spatial time series modeling for fMRI data analysis
The main point of interest in this book is to show that the same data can be treated using both a dynamical system and time series approach so that the neural and physiological information can be extracted more efficiently. Of course, time series modeling is valid not only in neuroscience data analysis but also in many other sciences and engineering fields where the statistical inference from the observed time series data plays an important role.
Автор: Chi Ronghu, Lin Na, Zhang Huimin Название: Discrete-Time Adaptive Iterative Learning Control: From Model-Based to Data-Driven ISBN: 9811904634 ISBN-13(EAN): 9789811904639 Издательство: Springer Рейтинг: Цена: 121110.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: The discrete-time adaptive iterative learning control (DAILC) is discussed as a cutting-edge of ILC and can address random initial states, iteration-varying targets, and other non-repetitive uncertainties in practical applications.
Автор: Juana Sanchez Название: Time Series for Data Scientists: Data Management, Description, Modeling and Forecasting ISBN: 1108837778 ISBN-13(EAN): 9781108837774 Издательство: Cambridge Academ Рейтинг: Цена: 63350.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Learn by doing with this user-friendly introduction to time series data analysis in R. This book explores the intricacies of managing and cleaning time series data of different sizes, scales and granularity, data preparation for analysis and visualization, and different approaches to classical and machine learning time series modeling and forecasting. A range of pedagogical features support students, including end-of-chapter exercises, problems, quizzes and case studies. The case studies are designed to stretch the learner, introducing larger data sets, enhanced data management skills, and R packages and functions appropriate for real-world data analysis. On top of providing commented R programs and data sets, the book's companion website offers extra case studies, lecture slides, videos and exercise solutions. Accessible to those with a basic background in statistics and probability, this is an ideal hands-on text for undergraduate and graduate students, as well as researchers in data-rich disciplines
Автор: Chi Название: Data-Driven Iterative Learning Control for Discrete-Time Systems ISBN: 9811959498 ISBN-13(EAN): 9789811959493 Издательство: Springer Рейтинг: Цена: 139750.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book belongs to the subject of control and systems theory. It studies a novel data-driven framework for the design and analysis of iterative learning control (ILC) for nonlinear discrete-time systems. A series of iterative dynamic linearization methods is discussed firstly to build a linear data mapping with respect of the system’s output and input between two consecutive iterations. On this basis, this work presents a series of data-driven ILC (DDILC) approaches with rigorous analysis. After that, this work also conducts significant extensions to the cases with incomplete data information, specified point tracking, higher order law, system constraint, nonrepetitive uncertainty, and event-triggered strategy to facilitate the real applications. The readers can learn the recent progress on DDILC for complex systems in practical applications. This book is intended for academic scholars, engineers, and graduate students who are interested in learning control, adaptive control, nonlinear systems, and related fields.
Автор: Chi Название: Discrete-Time Adaptive Iterative Learning Control ISBN: 9811904669 ISBN-13(EAN): 9789811904660 Издательство: Springer Рейтинг: Цена: 121110.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book belongs to the subject of control and systems theory. The discrete-time adaptive iterative learning control (DAILC) is discussed as a cutting-edge of ILC and can address random initial states, iteration-varying targets, and other non-repetitive uncertainties in practical applications. This book begins with the design and analysis of model-based DAILC methods by referencing the tools used in the discrete-time adaptive control theory. To overcome the extreme difficulties in modeling a complex system, the data-driven DAILC methods are further discussed by building a linear parametric data mapping between two consecutive iterations. Other significant improvements and extensions of the model-based/data-driven DAILC are also studied to facilitate broader applications. The readers can learn the recent progress on DAILC with consideration of various applications. This book is intended for academic scholars, engineers and graduate students who are interested in learning control, adaptive control, nonlinear systems, and related fields.
Автор: Guy Cohen; Jean-Pierre Quadrat Название: 11th International Conference on Analysis and Optimization of Systems: Discrete Event Systems ISBN: 3540198962 ISBN-13(EAN): 9783540198963 Издательство: Springer Рейтинг: Цена: 81050.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: The conference, coorganized by INRIA and Ecole des Mines de Paris, focuses on Discrete Event Systems (DES) and is aimed at engineers, scientists and mathematicians working in the fields of Automatic Control, Operations Research and Statistics who are interested in the modelling, analysis and optimization of DES.
Автор: Jerzy Tyszer Название: Object-Oriented Computer Simulation of Discrete-Event Systems ISBN: 1461372879 ISBN-13(EAN): 9781461372875 Издательство: Springer Рейтинг: Цена: 214280.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Object-Oriented Computer Simulation of Discrete-Event Systems offers a comprehensive presentation of a wide repertoire of computer simulation techniques available to the modelers of dynamic systems.
Автор: A. Wojtkiewicz Roger Название: Elementary Regression Modeling ISBN: 1506303471 ISBN-13(EAN): 9781506303475 Издательство: Sage Publications Рейтинг: Цена: 88710.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This user-friendly text builds on simple differences between groups to explain regression and regression modeling and provides a conceptual basis for the processes and procedures researchers follow when conducting regression analyses.
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