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Identification of Continuous-time Models from Sampled Data

This is the first book dedicated to direct continuous-time model identification for 15 years. It cuts down on time spent hunting through;

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Sampled-Data Models for Linear and Nonlinear Systems

themselves familiar. Rather than emphasising the differences between sampled-data and continuous-time systems, the authors proceed from the premise;

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Control of Uncertain Sampled-Data Systems

of sys tems control theory. Here, sampled-data system refers to the hybrid sys tem formed when continuous time and discrete time systems are;

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Continuous Time Modeling in the Behavioral and Related Sciences

in continuous time modeling, from approaches that closely mimic traditional linear discrete time models to highly nonlinear state space modeling;

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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®

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

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Networked Control Under Communication Constraints

presence of scheduling protocols. The book starts from a comprehensive introduction to three main approaches to sampled-data and networked control;

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Networked Control Under Communication Constraints

presence of scheduling protocols. The book starts from a comprehensive introduction to three main approaches to sampled-data and networked control;

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Linear Parameter-varying System Identification

researchers, the book contains twelve chapters, focusing on the most recent LPV identification methods for both discrete-time and continuous-time;

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Identification of Continuous-Time Systems

. In this book: Identification of Continuous-Time Systems-Linear and Robust Parameter Estimation, Allamaraju Subrahmanyam and Ganti Prasada Rao;

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Identification Of Dynamic Systems

or process identification. Both offline and online methods are presented, i.e. methods that post-process the measured data as well as methods;

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Modelling of Series Resonant Inverter

transformation. A generalized algorithm for power series method is suggested for getting inverse z - transform, to obtain sampled data of the response;

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A First Course in Control System Design

of sampled-data systems Compensator design with frequency response methods;

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Statistical Inference for Diffusion Type Processes

observations of the phenomenon in question. Data collection, model building and inference from the data collected, validation of the model and;

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A First Course in Control System Design

design in the state-space - Control design of sampled-data systems - Compensator design via frequency response modification;

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Process Identification and PID Control

industry. It includes several important identification algorithms to obtain frequency models or continuous-time/discrete-time transfer function;

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Aircraft and Rotorcraft System Identification

transport aircraft, and the detailed methodology to develop a continuous full flight envelope simulation model from individual system identification;

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Modelling Stock Market Volatility

Finance professionals in government and in the trading and investment banking industry use time models to provide necessary data for;

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Models for Dependent Time Series

, applicable, and statistically valid conclusions from multivariate (or vector) time series data. The first four chapters discuss the two main;

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Models for Dependent Time Series

, applicable, and statistically valid conclusions from multivariate (or vector) time series data. The first four chapters discuss the two main;

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Option Pricing and Estimation of Financial Models with R

series with continuous models, how to calibrate them from discrete data and further covers option pricing with one or more underlying assets;

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Data Analytic Techniques for Dynamical Systems

issues and analyses pertinent to understanding psychological data from a dynamical system perspective. Dynamical systems analysis (DSA;

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Analysis Of Longitudinal Data 2nd

of longitudinal data, it covers both the underlying statistical theory of each method, and its application to a range of examples from the agricultural;

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Analysis Of Longitudinal Data

of longitudinal data, it covers both the underlying statistical theory of each method, and its application to a range of examples from the agricultural;

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Control Engineering

This book offers fundamental information on the analysis and synthesis of continuous and sampled data control systems. It includes all the;

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Data Analytic Techniques for Dynamical Systems

issues and analyses pertinent to understanding psychological data from a dynamical system perspective. Dynamical systems analysis (DSA;

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Regression Models For Time Series Analysis

series analysis for over a century. Recently, new developments have made major strides in such areas as non-continuous data where a linear model;

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