Data clustering is typically considered a subjective process, which makes it problematic. For instance, how does one make statistical inferences based on clustering? The matter is di erent with pattern classiΓΏcation, for which two fundamental characteristics can be stated: (1) the error of a classiΓΏ
A probabilistic theory of random maps
β Scribed by O. Elbeyli; J.Q. Sun
- Publisher
- Elsevier Science
- Year
- 2005
- Tongue
- English
- Weight
- 399 KB
- Volume
- 10
- Category
- Article
- ISSN
- 1007-5704
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β¦ Synopsis
We present a probabilistic theory of random maps with discrete time and continuous state. The forward and backward Kolmogorov equations as well as the FPK equation governing the evolution of the probability density function of the system are derived. The moment equations of arbitrary order are derived, and the reliability and first passage time problem are also studied. Examples are presented to demonstrate the application of the theoretical development. Numerical solutions including the time histories of moment evolution, steady state probability density function, reliability and first passage time probability density function for time discrete random maps are included. The present work compliments the existing theory of continuous time stochastic processes.
π SIMILAR VOLUMES
In this article we prove the regularity of weakly biharmonic maps of domains in Euclidean four space into spheres, as well as the corresponding partial regularity result of stationary biharmonic maps of higher-dimensional domains into spheres.