Title :
Distributed Filtering Using Set Models With Confidence Values
Author_Institution :
Department of Electrical Engineering, Wright State University, Dayton, OH 45435
Abstract :
This paper describes an algorithm of distributed filtering using set models with confidence values. No statistics of noise distribution are needed. The only information required is the sets with confidence values from which the modeling and measurement errors and the initial values are obtained. Therefore, the algorithm has great potential for real-world applications.
Keywords :
Distributed algorithms; Filtering algorithms; Gaussian processes; Kalman filters; Smoothing methods; Statistical distributions; Statistics; Stochastic processes;
Conference_Titel :
American Control Conference, 1992
Conference_Location :
Chicago, IL, USA
Print_ISBN :
0-7803-0210-9
