A nonlinear adaptive estimation method based on local approximation

Author

Iiguni, Youji ; Kawamoto, Isao ; Adachi, Norihiko

Author_Institution

Dept. of Commun. Eng., Osaka Univ., Japan

Volume

45

Issue

7

fYear

1997

fDate

7/1/1997 12:00:00 AM

Firstpage

1831

Lastpage

1841

Abstract

One of the most important problems in signal processing is to estimate the output for a query from the input/output (I/O) data seen so far. This paper presents a nonlinear adaptive estimation method based on the n-nearest neighbor approach. In this method, observed I/O data are stored in a database in the form of a X-dimensional binary digital search trie (k-D trie), and a nonlinear local model to answer each query is derived based on regularization theory. The database contents are efficiently time updated to follow nonstationary data. A storage procedure allowing a simple and efficient update is developed for reduction in processing time and storage requirement. The effectiveness of the proposed method is demonstrated with both simulation data and real speech signals

Keywords

adaptive estimation; adaptive signal detection; approximation theory; query processing; speech processing; tree searching; binary digital search trie; database; database contents; input/output data; local approximation; n-nearest neighbor approach; nonlinear adaptive estimation method; nonlinear local model; nonstationary data; observed I/O data; processing time reduction; query processing; real speech signals; regularization theory; signal processing; simulation data; storage procedure; storage requirement reduction; Adaptive estimation; Adaptive signal processing; Binary search trees; Degradation; Estimation theory; Linear approximation; Neural networks; Signal processing; Speech; Transaction databases;

fLanguage

English

Journal_Title

Signal Processing, IEEE Transactions on

Publisher

ieee

ISSN

1053-587X

Type

jour

DOI

10.1109/78.599952

Filename

599952