Data compression of nonlinear time series using a hybrid linear/nonlinear predictor

被引:1
|
作者
Izumi, Tetsuya
Iiguni, Youji [1 ]
机构
[1] Osaka Univ, Grad Sch Engn Sci, Toyonaka, Osaka 5608531, Japan
[2] Osaka Univ, Grad Sch Engn, Suita, Osaka 5650871, Japan
关键词
hybrid ADPCM; linear predictor; nonlinear predictor; database;
D O I
10.1016/j.sigpro.2005.11.013
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
This paper presents a hybrid ADPCM that combines linear and nonlinear predictors, so that the advantages of both predictors can be utilized. This method estimates the linear part of the observed signal by the linear predictor, and then compensates the linear prediction error by the database-based nonlinear predictor. We develop a database update procedure so that the database size is not monotonously increased and nonstationary signals can be treated. The hybrid ADPCM achieves faster processing speed than a single nonlinear ADPCM and better compression performance than a single linear ADPCM and a single nonlinear ADPCM. (c) 2005 Elsevier B.V. All rights reserved.
引用
收藏
页码:2439 / 2446
页数:8
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