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This paper considers the realization of an intelligent digital signal processing system for representing time series and its application to the classification of stock prices. The system utilizes an effective mechanism to detect the nonstationary part (transient waves) which includes important information on the time series based on the Gabor representation and the knowledge representation of waveforms using an expert system. In the subsystem for digital signal processing, an adaptive ARMA model is fitted to the time series obtained by subtracting the moving average from the original time series to generate the time series containing enhanced transient waves. The Gabor representation is applied to classify the kinds of transient waves. A set of codebooks for the spectrum of transient waves is used to identify the kind of transient wave. In the subsystem of the expert system, the characteristics of the time series obtained by digital signal processing and other features recognized by conventional methods such as trend lines are transferred to the frames so that the recognition rules of experts are applied to classify the time series. As an applications, 194 time series of stock prices are recognized and classified into 11 categories. [ABSTRACT FROM AUTHOR]

1. The composition of fatty acids (FA) from C14 to C18 was measured for edible seston and for individual Daphnia galeata, Diaphanosoma brachyurum and Eodiaptomus japonicus from Lake Biwa using a pyrolysis--gas chromatography (Py-GC) method. Based on the relative abundance of the FA, inter-and intraspecific differences in composition were examined. 2. Among the FA, C16 : 0 was the most abundant, both in the three zooplankton species and in edible seston smaller than 20 μm, suggesting that the composition of the zooplankton was roughly reflected by their diet. However, the abundance of C18 : 1 relative to C16 : 1 and C18 : 0 was much higher in each zooplankton species than in the diet. 3. Comparison of the relative abundance of FA among the three zooplankton species revealed that intraspecific differences in FA composition are greater than interspecific differences. These results indicate that variability in FA composition is not necessarily species-specific, and can be obscured by variation in composition between individuals. [ABSTRACT FROM AUTHOR]