Anytime Evaluation of Regression-Type Algorithms

Regression-type algorithms are widely used for system modeling and characterization. There are applications where such characterizations are to be performed “on-line” to support control mechanisms and other decisions. In embedded autonomous systems robustness considerations ask for techniques, which, in addition to reflecting the actual state of the system and its environment, can continuously provide immediate signal processing results even in case of abrupt changes and/or temporal shortage of computational power and/or loss of some data. With other words in such situations the actual processing should be continued to insure appropriate performance. Consequently there is a need for robust techniques called “anytime” algorithms, which can provide Varkonyi-Koczy, A.R., T. Kovacshazy, O. Takacs, and Cs. Benedecsik, “Anytime Evaluation of Regression-Type Algorithms.” International Journal of Advanced Computational Intelligence, Vol. 5, No. 1, pp. 2-7, Feb. 2001. short response time and be very flexible with respect to the available input information and computational power. The paper presents some considerations concerning such flexibility in the case of regression-type algorithms.