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Other topics include Kalman filtering for systems with correlated noise or colored noise, limiting Kalman filtering for time-invariant systems, extended Kalman filtering for nonlinear systems, interval Kalman filtering for uncertain systems, and wavelet Kalman filtering for multiresolution analysis of random signals.
A knowledge of linear systems provides a firm foundation for the study of optimal control theory and many areas of system theory and signal processing.
This textbook, apart from introducing the basic aspects of applied mathematics, focuses on recent topics such as information data manipulation, information coding, data approximation, data dimensionality reduction, data compression, time-frequency and time scale bases, image manipulation, and image noise removal. data compression and noise removal.
"Signal Processing and Systems Theory" is concerned with thestudy of H-optimization for digital signal processing anddiscrete-time control systems.
Subject of multivariate splines presented from an elementary point of view; includes many open problems.
Other topics include Kalman filtering for systems with correlated noise or colored noise, limiting Kalman filtering for time-invariant systems, extended Kalman filtering for nonlinear systems, interval Kalman filtering for uncertain systems, and wavelet Kalman filtering for multiresolution analysis of random signals.
Discrete H? Optimization is concerned with the study of H? optimization for digital signal processing and discrete-time control systems.
Written for anyone who wants to learn about using wavelets to analyse, process, and synthesize images and signals. Applications are described in detail and there are step-by-step instructions about how to construct and apply wavelets. It is the only mathematically-rigorous monograph written by a mathematician specifically for nonspecialists.
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