Title :
Generation of random points uniformly distributed in hyperellipsoids
Author_Institution :
Dept. of Electr. & Syst. Eng., Connecticut Univ., Storrs, CT, USA
Abstract :
A precise and efficient algorithm for generating random points uniformly distributed in an arbitrary hyperellipsoid of dimension n is presented. Both the spherical coordinate and the Cartesian coordinate versions are given. Such random points are essential in the Monte Carlo method for numerical integration and in Monte Carlo simulations for the study and design of stochastic systems, especially in target tracking. The algorithm can also be used to generate random points uniformly distributed in a sector of a hyperellipsoid efficiently
Keywords :
Monte Carlo methods; computational geometry; integration; matrix algebra; random number generation; Cartesian coordinate; Monte Carlo method; hyperellipsoids; numerical integration; random points generation; spherical coordinate; stochastic systems; target tracking; Area measurement; Contracts; Covariance matrix; Distributed power generation; Ellipsoids; Particle measurements; Random number generation; Stochastic systems; Systems engineering and theory; Target tracking;
Conference_Titel :
Control Applications, 1992., First IEEE Conference on
Conference_Location :
Dayton, OH
Print_ISBN :
0-7803-0047-5
DOI :
10.1109/CCA.1992.269770
