1982Electronics and Communications in Japan (Part I Communications)Requires access

ϵ‐separating nonlinear digital filter and its applications

Hiroshi Harashima, Kaoru Odajima, Yoshiaki Shishikui, Hiroshi Miyakawa

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Abstract

Abstract This paper proposes an ϵ‐separating nonlinear digital filter (called an ϵ‐filter). This filter is intended for effective filtering of low‐amplitude noise superposed on the signal with sharp discontinuities and can be realized by combining a simple nonlinear element with a conventional linear filter. In this paper, the basic ϵ‐filter and its modifications to a trend‐adaptive filter and a two‐dimensional filter are described. The effectiveness of the new filter is demonstrated by computer simulation. Some of its application to EEG analysis, image processing and coding are also presented.

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What this paper is about

Abstract This paper proposes an ϵ‐separating nonlinear digital filter (called an ϵ‐filter). This filter is intended for effective filtering of low‐amplitude noise superposed on the signal with sharp discontinuities and can be realized by combining a simple nonlinear element with a conventional linear filter. In this paper, the basic ϵ‐filter and its modifications to a trend‐adaptive filter and a two‐dimensional filter are described. The effectiveness of the new filter is demonstrated by computer simulation. Some of its application to EEG analysis, image processing and coding are also presented.

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Available abstract

Abstract This paper proposes an ϵ‐separating nonlinear digital filter (called an ϵ‐filter). This filter is intended for effective filtering of low‐amplitude noise superposed on the signal with sharp discontinuities and can be realized by combining a simple nonlinear element with a conventional linear filter. In this paper, the basic ϵ‐filter and its modifications to a trend‐adaptive filter and a two‐dimensional filter are described. The effectiveness of the new filter is demonstrated by computer simulation. Some of its application to EEG analysis, image processing and coding are also presented.

Key concepts: Root-raised-cosine filter, Adaptive filter, Kernel adaptive filter, Filter design, Nonlinear filter, Filter (signal processing), Raised-cosine filter, Computer science

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