DocumentCode :
3564807
Title :
Univariate Function Decomposition via Tridiagonal Vector Enhanced Multivariance Products Representation (TVEMPR)
Author :
Gurvit, Ercan ; Baykara, N.A. ; Demiralp, Metin
Author_Institution :
Dept. of Math., Marmara Univ., Istanbul, Turkey
fYear :
2014
Firstpage :
189
Lastpage :
194
Abstract :
This work is devoted to the decomposition of a univariate function by using very recently developed Tridiagonal Vector Enhanced Multivariance Products Representation (TVEMPR). To this end the target function is expressed as a bilinear form over the power vector of the independent variable and the function´s coefficient vector. Both vectors are composed of denumerable infinite number of elements. The power vector of the independent variable is decomposed via Tridiagonal Vector Enhanced Multivariance Products Representation. The core matrix of the decomposition contains a 2×2 type left uppermost block as the only nonzero agent. Then the bilinear form, and therefore the function can be expressed thoroughly to get a decomposition as a linear combination of certain functions which are in fact derived from the original target function. This is the simplest case. Some other but complicated cases which start with multi outer products are left to future works. The support vectors have been chosen as proportional to certain power vectors of some given parameters to proceed from rather simplicity.
Keywords :
function approximation; vectors; TVEMPR; power vector; tridiagonal vector enhanced multivariance products representation; univariate function decomposition; Additives; Equations; Matrix decomposition; Optimization; Support vector machines; Vectors;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Mathematics and Computers in Sciences and in Industry (MCSI), 2014 International Conference on
Print_ISBN :
978-1-4799-4744-7
Type :
conf
DOI :
10.1109/MCSI.2014.24
Filename :
7046181
Link To Document :
بازگشت