标题：Least Squares Support Vector Machine Based on Wavelet-Neuron/ Uz wavelet neironiem balstītā minimālo kvadrātu atbalsta vektoru mašīna/ Машина опорных векторов наименьших квадратов на основе вэйвлет-нейрона
期刊名称：Information Technology and Management Science
印刷版ISSN：2255-9086
电子版ISSN：2255-9094
出版年度：2014
卷号：17
期号：1
页码：19-24
DOI：10.1515/itms-2014-0002
语种：English
出版社：Walter de Gruyter GmbH
摘要：In this paper, a simple wavelet-neuro-system that implements learning ideas based on minimization of empirical risk and oriented on information processing in on-line mode is developed. As an elementary block of such systems, we propose using wavelet-neuron that has improved approximation properties, computational simplicity, high learning rate and capability of local feature identification in data processing. The architecture and learning algorithm for least squares wavelet support machines that are characterized by high speed of operation and possibility of learning under conditions of short training set are proposed.
关键词：Adaptive wavelet function ; forecasting ; least squares support vector machine ; non-linear non-stationary time series ; wavelet-neuron
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