Dynamical Systems in Description of Nonlinear Recursive Regression Transformers


Autoria(s): Kirichenko, Mykola; Donchenko, Volodymyr; Serbaev, Denys
Data(s)

19/12/2009

19/12/2009

2006

Resumo

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.

Identificador

1313-0463

http://hdl.handle.net/10525/726

Idioma(s)

en

Publicador

Institute of Information Theories and Applications FOI ITHEA

Palavras-Chave #Empirical Functions #Learning Samples #Beam Dynamics with Delay #Recursive Nonlinear Regressive Transformer #Generalized Inverse #Least Square Method
Tipo

Article