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Mastering System Identification in 100 Exercises

This book enables readers to understand system identification and linear system modeling through 100 practical exercises without requiring;

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Blind Identification of Structured Dynamic Systems

This book is intended for researchers active in the field of (blind) system identification and aims to provide new identification ideas;

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Subspace Methods for System Identification

An in-depth introduction to subspace methods for system identification in discrete-time linear systems thoroughly augmented with advanced;

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Aircraft and Rotorcraft System Identification

, Aircraft and Rotorcraft System Identification, Second Edition addresses the entire process of aircraft and rotorcraft system identification from;

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Advanced Nonlinear Strategies for Vibration Mitigation and System Identification

The papers in this volume address advanced nonlinear topics in the general areas of vibration mitigation and system identification, such as;

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System Identification

System Identification shows the student reader how to approach the system identification problem in a systematic fashion. The process;

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Linear Parameter-varying System Identification

This review volume reports the state-of-the-art in Linear Parameter Varying (LPV) system identification. Written by world renowned;

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Nonparametric System Identification

Presenting a thorough overview of the theoretical foundations of non-parametric system identification for nonlinear block-oriented systems;

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Nonparametric System Identification

Presenting a thorough overview of the theoretical foundations of non-parametric system identification for nonlinear block-oriented systems;

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System Identification

Appropriate for courses in System Identification. This book is a comprehensive and coherent description of the theory, methodology and;

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Blind Equalization and System Identification

common characteristics of these algorithms as well as learning from their different perspectives. Blind Equalization and System Identification;

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Combined Parametric-Nonparametric Identification of Block-Oriented Systems

This book considers a problem of block-oriented nonlinear dynamic system identification in the presence of random disturbances. This class;

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System Identification

System identification is a general term used to describe mathematical tools and algorithms that build dynamical models from measured data;

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Iris Recognition

Iris recognition has received increasing attention recently in the world. A biometric system provides automatic identification of an;

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Control System Analysis and Identification with MATLAB (R)

identification of linear time-invariant systems, scaled system, and sampled-data system Presents an overview of piecewise constant;

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Control System Analysis and Identification with MATLAB®

Discusses 'functions related to block pulse functions' extensively along with their applications Contains analysis and identification;

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Control Oriented Modelling & Identificat

-based model reduction techniques; integrated modelling and parameter estimation; identification for robust control of complex systems; subspace;

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The CARICOM System

agreements encompassing the basis of regional cooperation through identification of legal regimes expressed to constitute the CARICOM System.;

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Proceedings of the ASME 2013 Dynamics Systems and Control Conference-(DSCC2013)

Manipulators Robotics and Manipulators Sensing System Identification and Estimation for Automotive Applications System Identification and Modeling;

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Impacts of Customer Relationship Management on Development of Corporations

The overall goal of this book is the identification of design features and prerequisites for a CRM-system, which contribute to an increase;

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Functional Fractional Calculus for System Identification and Controls

particularly for system identification, description and then efficient controls. The reader gets a feeling of the wide applicability of fractional;

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Identification Of Physical Systems

Identification of a physical system deals with the problem of identifying its mathematical model using the measured input and output data;

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Regularized System Identification

power of machine learning without losing sight of the system-theoretical principles of black-box identification. The authors' reformulation;

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