Accession Number : ADA115161
Title : A Class of FFT Based Algorithms for Linear Estimation.
Descriptive Note : Technical rept.,
Corporate Author : CALIFORNIA UNIV DAVIS SIGNAL AND IMAGE PROCESSING LAB
Personal Author(s) : Jain,Anil K ; Jasiulek,Joachim
PDF Url : ADA115161
Report Date : Apr 1982
Pagination or Media Count : 77
Abstract : In the past two decades since the advent of Kalman's recursive filter, numerous algorithms for linear estimation have emerged. Most of these algorithms are recursive and rely on solving a Riccati equation or equivalent recursive equations. It will be shown how some of the classical problems such as Linear Smoothing and Recursive Block Filtering problems can be solved exactly by some new nonrecursive algorithms which are based on the Fast Fourier Transform (FFT). Moreover, these algorithms are readily modified to generate the Riccati matrix at specified times, if this is desired. These results are then extended to a block filtering algorithm, where data is received and smoothed recursively block by block. Real time batch processing applications include image processing and array processing of signals.
Descriptors : *Algorithms, *Estimates, *Linear algebraic equations, *Image processing, Matrices(Mathematics), Fast Fourier transforms, Recursive functions, *Image processing, Riccati equation, Arrays, Filters, Recursive filters, Real time
Subject Categories : Theoretical Mathematics
Distribution Statement : APPROVED FOR PUBLIC RELEASE