M. Haseyama et al., RELATION BETWEEN RLS AND ARMA LATTICE FILTER REALIZATION-ALGORITHM AND ITS APPLICATION, IEICE transactions on fundamentals of electronics, communications and computer science, E77A(5), 1994, pp. 839-846
Citations number
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Categorie Soggetti
Engineering, Eletrical & Electronic","Computer Science Hardware & Architecture","Computer Science Information Systems
In this paper, the relationship between the recursive least square (RL
S) method with a U-D decomposition algorithm and ARMA lattice filter r
ealization algorithm is presented. Both the RLS method and the lattice
filter realization algorithm are used for the same applications, such
as model identification, etc, therefore, it is expected that the latt
ice filter algorithm is in some ways related to the RLS. Though some o
f the proposed lattice filter algorithms have been derived by the RLS
method, they do not express the relationship between RLS and ARMA latt
ice filter realization algorithm. In order to describe the relation cl
early, a new structure of ARMA lattice fitter is proposed. Further, ba
sed on the relationship, a method of model identification with frequen
cy weighting (MIFW), which is different from a previous method, is der
ived. The new MIFW method modifies the lattice parameters which are ac
quired without a frequency weighting and obtain the parameters of an A
RMA model, which is identified with frequency weighting. The proposed
MIFW method has the following restrictions: (1) The used frequency wei
ghting is FIR filter with a low order. (2) By using the parameters of
the ARMA lattice filter with ARMA (N,M) order and the frequency weight
ing with L order, the new ARMA parameter with the frequency weighting
is with ARMA(N-L,M-L) order. By using the proposed MIFW method, the AR
MA parameters estimated with the frequency weighting can be obtained w
ithout starting the computation again.