DocumentCode :
734151
Title :
A neural network based algorithm to compute the distance between a point and an ellipsoid
Author :
Shenshen Gu ; Jiao Peng
Author_Institution :
Sch. of Mechatron. Eng. & Autom., Shanghai Univ., Shanghai, China
fYear :
2015
fDate :
27-29 March 2015
Firstpage :
294
Lastpage :
299
Abstract :
In this paper, we proposed a recurrent neural network to compute the distance between a point to an ellipsoid in n spatial dimensions. So far, the problem used to be solved by traditional mathematical algorithms, which is either too slow in computing time or too one-sided in applications. Our proposed neural network, which makes use of a cost gradient projection onto the tangent space of the constraints, not only suitable for the two dimensions problems and three dimensions problems but also can compute the distance from a point to a hyperellipsoid. The numerical results shows that the proposed method is efficient and effective.
Keywords :
gradient methods; mathematics computing; nonlinear programming; recurrent neural nets; cost gradient projection; hyperellipsoid; nonlinear optimization; recurrent neural network; Algebra; Control theory; Iterative methods; Stability;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Advanced Computational Intelligence (ICACI), 2015 Seventh International Conference on
Conference_Location :
Wuyi
Print_ISBN :
978-1-4799-7257-9
Type :
conf
DOI :
10.1109/ICACI.2015.7184717
Filename :
7184717
Link To Document :
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