Title :
Neural implementation of Karmarkar algorithm
Author :
Sridhar, P. ; Pujari, Arun K.
Author_Institution :
Sch. of Math. & Comput. Sci., Hyderabad Univ.
Abstract :
The Karmarkar algorithm performs a sequence of projective transformations each followed by optimization over an inscribed sphere and then inverse projective transformation. These steps are implemented on the authors´ model with two neural-like circuits, one embedded inside the other. The inner circuit finds least square error solutions using the complementary slackness condition. The outer circuit finds a novel interior primal solution using the delta rule by making use of the error in the computation of dual solution. This circuit exhibits potential for applications where real-time optimization is required-as is the case in robotics, satellite guidance, etc
Keywords :
least squares approximations; linear programming; neural nets; optimisation; Karmarkar algorithm; complementary slackness condition; delta rule; inscribed sphere; interior primal solution; inverse projective transformation; least square error solutions; linear programming; neural-like circuits; optimization; projective transformations; real-time optimization; robotics; satellite guidance; Application software; Artificial neural networks; Biological neural networks; Brain modeling; Circuits; Computer vision; Constraint optimization; Mathematics; Neurons; Sequences;
Conference_Titel :
Circuits and Systems, 1991., IEEE International Sympoisum on
Print_ISBN :
0-7803-0050-5
DOI :
10.1109/ISCAS.1991.176692