IMI-BAS
 

BulDML at Institute of Mathematics and Informatics >
ITHEA >
International Journal ITA >
2006 >
Volume 13 Number 1 >

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, Mykola
Donchenko, Volodymyr
Serbaev, Denys
Keywords: Empirical Functions
Learning Samples
Beam Dynamics with Delay
Recursive Nonlinear Regressive Transformer
Generalized Inverse
Least 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

Files in This Item:

File Description SizeFormat
ijita13-1-p07.pdf125.38 kBAdobe PDFView/Open

 



Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.

 

Valid XHTML 1.0! DSpace Software Copyright © 2002-2009  The DSpace Foundation - Feedback