Please use this identifier to cite or link to this item: http://hdl.handle.net/10525/726

 Title: Dynamical Systems in Description of Nonlinear Recursive Regression Transformers Authors: Kirichenko, MykolaDonchenko, VolodymyrSerbaev, Denys Keywords: Empirical FunctionsLearning SamplesBeam Dynamics with DelayRecursive Nonlinear Regressive TransformerGeneralized InverseLeast Square Method Issue Date: 2006 Publisher: Institute of Information Theories and Applications FOI ITHEA Abstract: The task of approximation-forecasting for a function, represented by empirical data was investigated. Certain class of the functions as forecasting tools: so called RFT-transformers, – was proposed. Least Square Method and superposition are the principal composing means for the function generating. Besides, the special classes of beam dynamics with delay were introduced and investigated to get classical results regarding gradients. These results were applied to optimize the RFT-transformers. The effectiveness of the forecast was demonstrated on the empirical data from the Forex market. URI: http://hdl.handle.net/10525/726 ISSN: 1313-0463 Appears in Collections: Volume 13 Number 1

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