Search for dissertations about: "Forgetting Factor"
Showing result 1 - 5 of 8 swedish dissertations containing the words Forgetting Factor.
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1. On Parameter Estimation and Control of Time-Varying Stochastic Systems
Abstract : This thesis is about parameter estimation and control of time-varying stochastic systems. It can be divided into two parts. The first part deals with an estimation algorithm commonly used when estimating parameters in time-varying stochastic systems, the Recursive Least Squares (RLS) algorithm with forgetting factor. READ MORE
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2. Adaptive Forgetting through Multiple Models and Adaptive Control of Car Dynamics
Abstract : A new recursive identif ication method, Adaptive Forgetting through Multiple Models - AFMM, is presented and evaluated using computer simulations. AFMM is specif ically suited for identification of systems with jumping or rapidly changing parameters. READ MORE
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3. Frequency Domain Aspects of Modeling and Control in Adaptive Systems
Abstract : In this thesis various aspects of modeling and control in adaptive systems are presented from a frequency domain viewpoint.The thesis consists of three parts, where the first part contains a general introduction and background information concerning the problems that will be treated. READ MORE
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4. Fast Algorithms for Integral Equations and Least Squares Identification Problems
Abstract : This work is concerned with fast algorithms for integral equations and least squares identification problems.The presentation is divided into three parts. In the first part a fast algorithm for solving systems oflinear equations with a matrix that is alm ost Toeplitz is derived and applied to Fredholm integral equations with stationary kernels. READ MORE
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5. On System Identification in one and two Dimensions with Signal Processing Applications
Abstract : This thesis consists of four parts, with system identification as the common theme. The first part studies the asymptotic properties of two-dimensional identification methods. In the second part an approach to identification of time varying systems is presented. READ MORE