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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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Applied Parameter Estimation for Chemical Engineers

important optimization methods used for parameter estimation. It focuses on the Gauss-Newton method and its modifications for systems and processes;

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Applied Parameter Estimation for Chemical Engineers

important optimization methods used for parameter estimation. It focuses on the Gauss-Newton method and its modifications for systems and processes;

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Modelling and Parameter Estimation of Dynamic Systems

networks are finding more and more use in parameter estimation problems. Modelling and Parameter Estimation of Dynamic Systems presents a detailed;

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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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Power System State Estimation

overview of power system operation and the role of state estimation in overall energy management. It uses an abundance of examples, models, tables;

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Item Response Theory

chapters discussing parameter estimation with multiple groups, parameter estimation for a test with mixed item types, and Markov chain Monte Carlo;

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Classification, Parameter Estimation and State Estimation

of contemporary state estimation techniques vs older content of particle filter methods * The latest techniques for classification and supervised learning;

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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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Applied State Estimation and Association

6 focus on solving the problem of estimation with a single sensor observing a single object, and cover such topics as parameter estimation;

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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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Weibull Models

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

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Efficient Approaches to Source Localization and Parameter Estimation

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Efficient Approaches to Source Localization and Parameter Estimation

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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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Inference in Hidden Markov Models

range from filtering and smoothing of the hidden Markov chain to parameter estimation, Bayesian methods and estimation of the number of states;

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Density Ratio Estimation in Machine Learning

, independent component analysis, clustering, classification and conditional density estimation can be systematically solved via the estimation;

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Density Ratio Estimation in Machine Learning

, independent component analysis, clustering, classification and conditional density estimation can be systematically solved via the estimation;

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Kinetic Parameter Estimation in Prepackaged Foods Subjected to Dynamic Thermal Treatments

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Kinetic Parameter Estimation in Prepackaged Foods Subjected to Dynamic Thermal Treatments

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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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Statistical Estimation for Truncated Exponential Families

focuses on a truncated exponential family of distributions with a natural parameter and truncation parameter as a typical nonregular family. This;

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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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Introduction To Statistical Time Series

analysis Spectral theory and filtering Large sample theory Estimation of the mean and autocorrelations Estimation of the spectrum Parameter;

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Parameter Estimation For Scientists And Engineers

. Therefore one purpose of this book is to show that statistical parameter estimation has much more to offer than least squares estimation alone;

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