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Please use this identifier to cite or link to this item: http://eprint.iitd.ac.in/handle/2074/1762

Title: Multichannel time-varying ARMA model identification by least squares circular lattice structures
Authors: Chakraborty, M
Prasad, S
Keywords: adaptive autoregressive moving average (ARMA)
scalar computations
input vector
least squares circular lattice (LSCL)
lower-order ARMA
Issue Date: 1991
Citation: Acoustics, Speech, and Signal Processing, 5, 3229 - 3332p.
Abstract: An attempt is made to develop algorithms for the adaptive autoregressive moving average (ARMA) modeling of a linear, slowly time-varying, multichannel system using scalar computations only. The multivariate ARMA process is mapped to an equivalent scalar, periodic ARMA process. By properly defining the input and output vectors corresponding to the scalar process, the problem is formulated as the order-recursive computation of the orthogonal projection of the input vector on an appropriate data subspace. This is carried out by first orthogonalizing the data vectors through the Gram-Schmidt procedure resulting in the least squares circular lattice (LSCL) algorithm. The LSCL algorithm evaluated all possible lower-order ARMA lattice filters. It consists of several identical sections, one for each channel, pipelined in a circular manner, and is therefore well suited for implementation in modular architecture
URI: http://eprint.iitd.ac.in/dspace/handle/2074/1762
Appears in Collections:Electrical Engineering

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