Title :
Dynamical systems that sort lists, diagonalize matrices and solve linear programming problems
Author_Institution :
Div. of Appl. Sci., Harvard Univ., Cambridge, MA, USA
Abstract :
The author establishes a number of properties associated with the dynamical system H˙=[H,[H,N]], where H and N are symmetric n-by-n matrices and [A,B]=AB-BA. The most important of these come from the fact that this equation is equivalent to a certain gradient flow on the space of orthogonal matrices. Particular emphasis is placed on the role of this equation as an analog computer. For example, it is shown how to map the data associated with a linear programming problem into H(0) and N in such a way as to have H˙=[H[H,N]] evolve to a solution of the linear programming problem. This result can be applied to find systems that solve a variety of generic combinatorial optimization problems, and it also provides an algorithm for diagonalizing symmetric matrices
Keywords :
analogue computers; linear programming; mathematics computing; matrix algebra; sorting; analog computer; combinatorial optimization; diagonalize matrices; dynamical system; linear programming; lists sorting; mathematics computing; Analog computers; Computational complexity; Computer networks; Concurrent computing; Eigenvalues and eigenfunctions; Equations; Linear programming; Neural networks; Parallel processing; Symmetric matrices;
Conference_Titel :
Decision and Control, 1988., Proceedings of the 27th IEEE Conference on
Conference_Location :
Austin, TX
DOI :
10.1109/CDC.1988.194420