Statistical Interpolation of Non-Gaussian AR Stochastic Processes, M.Sc. Thesis Sharif University of Technology ; Amini, Arash (Supervisor)
Abstract
white noise or an innovation process through an all-pole filter. Applications of these processes include speech processing, RADAR signals and stock market data modeling. There exists an extensive research material on the AR processes with Gaussian innovation, however studies about the non-Gaussian case have been much more limited, while in many applications the asymptotic behavior of the signal is non-Gaussian. Non-Gaussian processes have an advantage over Gaussian ones in being capable of modeling sparsity. Assuming an appropriate non-Gaussian innovation one can suggest a more realistic description of sparse signals and predict their behavior or estimate their unknown values successfully....
Cataloging briefStatistical Interpolation of Non-Gaussian AR Stochastic Processes, M.Sc. Thesis Sharif University of Technology ; Amini, Arash (Supervisor)
Abstract
white noise or an innovation process through an all-pole filter. Applications of these processes include speech processing, RADAR signals and stock market data modeling. There exists an extensive research material on the AR processes with Gaussian innovation, however studies about the non-Gaussian case have been much more limited, while in many applications the asymptotic behavior of the signal is non-Gaussian. Non-Gaussian processes have an advantage over Gaussian ones in being capable of modeling sparsity. Assuming an appropriate non-Gaussian innovation one can suggest a more realistic description of sparse signals and predict their behavior or estimate their unknown values successfully....
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