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Modelling and Parameter Estimation of Dynamic Systems

Parameter estimation is the process of using observations from a system to develop mathematical models that adequately represent the system;

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Weibull Models

analysis, parameter estimation, model validation, and application; classifies the different models and their properties; intertwines theory and;

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Model Based Parameter Estimation

This judicious selection of articles combines mathematical and numerical methods to apply parameter estimation and optimum experimental;

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Principles and Applications of RELAX

The multiple signal demixing and parameter estimation problems that result from the impacts of background noise and interference are issues;

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Model-Based Processing for Underwater Acoustic Arrays

Kalman filter in its recursive estimator form. Examples of applications to localization, bearing estimation, range estimation and model parameter;

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Measurement Data Modeling and Parameter Estimation

Measurement Data Modeling and Parameter Estimation integrates mathematical theory with engineering practice in the field of measurement;

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Measurement Data Modeling and Parameter Estimation

Measurement Data Modeling and Parameter Estimation integrates mathematical theory with engineering practice in the field of measurement;

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Reduced Order Methods for Modeling and Computational Reduction

in real-time with applications in engineering; data assimilation, geometry registration, and parameter estimation with special attention to real;

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Advanced Linear Models

This work details the statistical inference of linear models including parameter estimation, hypothesis testing, confidence intervals, and;

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Mathematical Modeling in Chemical Engineering

asymptotic methods. An overview of solution methods for typical classes of models is given. As final steps in model building, parameter estimation;

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Optimal Design

in practice and it often happens that designs which are optimal for parameter estimation allow no possibility of model validation. For this reason the;

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Mixture Models and Applications

interesting and challenging problems such as parameters estimation, model selection, feature selection, etc. The goal of this book is to summarize the;

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Radar Remote Sensing for Crop Biophysical Parameter Estimation

of research techniques and their applicability for crop biophysical parameter estimation. It introduces theoretical background of radar scattering;

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Radar Remote Sensing for Crop Biophysical Parameter Estimation

of research techniques and their applicability for crop biophysical parameter estimation. It introduces theoretical background of radar scattering;

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Digital Processing of Random Signals

parameter estimation theory for Gaussian processes. Subsequent chapters explore autoregressive parameter estimation and its role in adaptive;

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Parameter Estimation in Fractional Diffusion Models

This book is devoted to parameter estimation in diffusion models involving fractional Brownian motion and related processes. For many years;

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Identification of Continuous-Time Systems

consider CT system models that are linear in their unknown parameters and propose robust methods of estimation. This book complements the existing;

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Item Response Theory

used to estimate the item or ability parameters under various IRT models. Extensively revised and expanded, this edition offers three new;

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Model Based Inference in the Life Sciences: A Primer on Evidence

text as it assumes reasonable competence in modeling and parameter estimation.;

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Parameter Estimation in Reliability and Life Span Models

Offers an applications-oriented treatment of parameter estimation from both complete and censored samples; contains notations, simplified;

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Methods of Statistical Model Estimation

Methods of Statistical Model Estimation examines the most important and popular methods used to estimate parameters for statistical models;

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Methods of Statistical Model Estimation

Methods of Statistical Model Estimation examines the most important and popular methods used to estimate parameters for statistical models;

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Applied Parameter Estimation for Chemical Engineers

This book determines adjustable parameters in mathematical models that describe steady state or dynamic systems, presenting the most;

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Applied Parameter Estimation for Chemical Engineers

This book determines adjustable parameters in mathematical models that describe steady state or dynamic systems, presenting the most;

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Bond Graph Modelling for Control, Fault Diagnosis and Failure Prognosis

This book shows in a comprehensive presentation how Bond Graph methodology can support model-based control, model-based fault diagnosis;

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Bond Graph Modelling for Control, Fault Diagnosis and Failure Prognosis

This book shows in a comprehensive presentation how Bond Graph methodology can support model-based control, model-based fault diagnosis;

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Efficient Approaches to Source Localization and Parameter Estimation

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