Learning and complexity minimization methods of diophantine and splines neural networks with self-organizing architecture

Author

Timofeyev, A.

Author_Institution

Inst. of Inf. & Autom., Acad. of Sci., St. Petersburg

fYear

1995

fDate

20-23 Sep 1995

Firstpage

217

Lastpage

225

Abstract

Diophantine neural networks described by polynomial and splines with integer paramaters are considered. Recurrent and non-recurrent learning algorithms and complexity minimization methods and self-organizing architecture of diophantine and splines neural networks are offered

Keywords

computational complexity; learning (artificial intelligence); multilayer perceptrons; recurrent neural nets; self-organising feature maps; splines (mathematics); complexity minimization methods; diophantine neural networks; nonrecurrent learning algorithms; recurrent learning algorithms; self-organizing architecture; splines neural networks; Equations; Minimization methods; Network synthesis; Neural networks;

fLanguage

English

Publisher

ieee

Conference_Titel

Neuroinformatics and Neurocomputers, 1995., Second International Symposium on

Conference_Location

Rostov on Don

Print_ISBN

0-7803-2512-5

Type

conf

DOI

10.1109/ISNINC.1995.480860

Filename

480860

Link To Document

https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=3069535