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Kalman Filtering and Neural Networks

expert contributors that discuss Kalman filtering as applied to the training and use of neural networks. Although the traditional approach to the;

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Kalman Filtering: With Real-Time Applications

This new edition presents a thorough discussion of the mathematical theory and computational schemes of Kalman filtering. The filtering;

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Kalman Filtering: With Real-Time Applications

This new edition presents a thorough discussion of the mathematical theory and computational schemes of Kalman filtering. The filtering;

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Approximate Kalman Filtering

Kalman filtering algorithm gives optimal (linear, unbiased and minimum error-variance) estimates of the unknown state vectors of a linear;

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Kalman Filtering

The purpose of the Kalman filter is to use measurements that are observed over time that contain noise (random variations) and other;

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Kalman Filtering

The definitive textbook and professional reference on Kalman Filtering fully updated, revised, and expanded This book contains the latest;

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Nonlinear Pinning Control of Complex Dynamical Networks

are based on determining a model for the unknow system using a recurrent neural network, using on-line extended Kalman filtering for learning;

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Discrete-Time Neural Observers

Discrete-Time Neural Observers: Analysis and Applications presents recent advances in the theory of neural state estimation for discrete;

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Learning Approaches in Signal Processing

forests, sparsity, and low-rank matrix estimation and cutting-edge visual/signal processing techniques, including face recognition, Kalman;

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Kalman Filtering Techniques for Radar Tracking

for eliminating the real-time execution of complete recursive Kalman filtering matrix equations that reduce tracking and update time. It also;

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Convolutional Neural Networks in Visual Computing

This book covers the fundamentals in designing and deploying techniques using deep architectures. It is intended to serve as a beginner's;

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Convolutional Neural Networks in Visual Computing

This book covers the fundamentals in designing and deploying techniques using deep architectures. It is intended to serve as a beginner's;

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Machine Learning

modelling are also considered in depth. This palette of techniques concludes with an extended chapter on neural networks and deep;

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Fundamentals of Kalman Filtering

Prize -- for the development and dissemination of the optimal digital technique (known as the Kalman Filter) that is pervasively used to control;

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Robust Kalman Filtering for Signals and Systems with Large Uncertainties

of robust control theory. One of the major developments of modern control theory was the Kalman Filter and hence the development of a robust version;

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Optimal Filtering

, and estimation; the discrete-time Kalman filter; time-invariant filters; properties of Kalman filters; computational aspects; and smoothing;

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Diffuse Algorithms for Neural and Neuro-Fuzzy Networks

Diffuse Algorithms for Neural and Neuro-Fuzzy Networks: With Applications in Control Engineering and Signal Processing presents new;

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Nonlinear Kalman Filtering for Force-Controlled Robot Tasks

This monograph focuses on how to achieve more robot autonomy by means of reliable processing skills. Nonlinear Kalman Filtering for Force;

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An Introduction to Kalman Filtering With Matlab Examples

state evolution and measurement processes are both linear and Gaussian. Given the ubiquity of such systems, the Kalman filter finds use in a;

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Kalman Filtering and Information Fusion

This book addresses a key technology for digital information processing: Kalman filtering, which is generally considered to be one of the;

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Kalman Filtering and Information Fusion

This book addresses a key technology for digital information processing: Kalman filtering, which is generally considered to be one of the;

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Nonlinear Filtering

dynamic control systems and system states and a brief description of the Kalman filter. In the following chapters, various state estimation;

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Adaptive Filtering

concepts. Examples address up-to-date problems drawn from actual applications. Several chapters are expanded and a new chapter 'Kalman Filtering;

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Adaptive Filtering

concepts. Examples address up-to-date problems drawn from actual applications. Several chapters are expanded and a new chapter 'Kalman Filtering;

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Digital Signal Processing in Telecommunications

This publication deals with the application of advanced digital signal processing techniques and neural networks to various;

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Measure Theory and Filtering

The estimation of noisily observed states from a sequence of data has traditionally incorporated ideas from Hilbert spaces and calculus;

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Measure Theory and Filtering

The estimation of noisily observed states from a sequence of data has traditionally incorporated ideas from Hilbert spaces and calculus;

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