Noise Reduction Method for Time Series Data of plant. Growth with Adjustment of Cut off Frequency of Low Pass Filter.

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  • SHIMIZU Hiroshi
    Division of Science and Technology of Graduate School of Agriculture, Kyoto University

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Other Title
  • ローパスフィルタ遮断周波数の調整による植物生長時系列データのノイズ除去法
  • ローパス フィルタ シャダン シュウハスウ ノ チョウセイ ニヨル ショクブツ

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Abstract

A new procedure for reducing the noise on time-series data is presented. Lowpass filters commonly are used for noise reduction, but high-frequency components such as plant elongation responses to sudden changes in environmental conditions also are removed. This phenomenon complicates analysis of data depicting plant responses to changes in environmental conditions.<BR>The procedure we developed consists of moving average noise reduction combined with numerical differentiation. The moving average is an all-encompassing method of noise reduction and is applied easily, the length of the symmetric moving average operator is adjusted according to a transition in the original time series. A second derivative is used to detect the transition in the original time series. It is assumed that a point in the original time-series with a large second-derivative value is likely the transition point. The length of the symmetric moving average operator is decreased when the second derivative is large and increased when the second derivative is small. Parameters of the developed procedure are the minimum and maximum values of the moving average operator length. These values affect noise reduction levels independently in the transition and stable domains.

Journal

  • Shokubutsu Kojo Gakkaishi

    Shokubutsu Kojo Gakkaishi 8 (4), 237-243, 1996

    JAPANESE SOCIETY OF AGRICULTURAL, BIOLOGICAL AND ENVIRONMENTAL ENGINEERS AND SCIENTISTS

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