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  5. The adaptive filter-predictor for multivariate essentially nonstationary time series

The adaptive filter-predictor for multivariate essentially nonstationary time series

Ye.V. Bodyanskiy, O.A. Romaniuk, O.S. Udovenko
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The adaptive forecasting task for multivariate time series whose characteristics can abruptly change in time by nonpredictable way is solved. The neural network architecture with synapses-dynamic filter is introduced and learning algorithm that combines both high speed and filtering properties is proposed. The proposed filter-predictor is intended for using in technical analysis tasks connected with on-line stock indexes prediction.
Keywords: adaptive prediction and filtering, adaptive multivariate nonstationary time series, learning
Reference:
Bodianskyi, E.V., Romaniuk, O.A. and Udovenko, O.S. (2009), "Adaptyvnыi fyltr-predyktor mnohomernыkh sushchestvenno nestatsyonarnыkh vremennыkh riadov" , Information Processing Systems, Vol. 4(78), pp. 23-27.