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Determinism Measurement in Time Series by Chaotic Approach and Its Applications
Yasunari Fujimoto and Tadashi Iokibe
Meidensha Corporation 36-2 Nihonbashi Hakozakicho, Chuo-ku, Tokyo 103-8515, Japan
Received:July 17, 1998Accepted:September 18, 1998Published:February 20, 1999
Keywords:Chaos, Trajectory parallel measurement, Time series analysis, Trajectory, Determinism, Stochastic process, Diagnosis, Automobile
Abstract
Frequently irregular-looking time series may have a deterministic cause, which is why it is called deterministic chaos. Even if a time series has a little noise, it is not always easy to recognize noise by looking at data. Fast Fourier transform (FFT) is used to extract characteristic frequencies. A chaotic time series consists of an infinite number of frequency elements, producing a broad continuous power spectrum but has few distinguishable characteristics. We propose a way, called trajectory parallel measurement (TPM), based on the chaotic approach to distinguish determinism and randomness in a time series, and apply this to a chaotic time series with random noise, summarizing the results of practical application in diagnosing automatic transmission.
Cite this article as:Y. Fujimoto and T. Iokibe, “Determinism Measurement in Time Series by Chaotic Approach and Its Applications,” J. Adv. Comput. Intell. Intell. Inform., Vol.3 No.1, pp. 50-55, 1999.Data files:
