Browsing by Subject "Maximum a posteriori probabilities"
Now showing items 1-5 of 5
-
Conference Object
Bounds on max-product algorithms for multiple fault diagnosis in graphs with loops
(Institute of Electrical and Electronics Engineers Inc., 2007)In this paper, we analyze the performance of algorithms that use belief propagation max-product iterations to solve the generalized multiple fault diagnosis (GMFD) problem. The GMFD problem is described by a bipartite ...
-
Conference Object
Bounds on the probability of misclassification among hidden Markov models
(2011)Given a sequence of observations, classification among two known hidden Markov models (HMMs) can be accomplished with a classifier that minimizes the probability of error (i.e., the probability of misclassification) by ...
-
Conference Object
Hidden markov model classification based on empirical frequencies of observed symbols
(IFAC Secretariat, 2014)Given a sequence of observations, classification among two known hidden Markov models (HMMs) can be accomplished with a classifier that minimizes the probability of error (i.e., the probability of misclassification) by ...
-
Conference Object
Improved performance bounds on max-product algorithms for multiple fault diagnosis in graphs with loops
(2008)In this paper, we analyze the performance of belief propagation max-product algorithms when used to solve the multiple fault diagnosis (MFD) problem. The MFD problem is described by a bipartite diagnosis graph (BDG) which ...
-
Conference Object
Low-complexity max-product algorithms for problems of multiple fault diagnosis
(2008)In this paper, we propose low-complexity max-product algorithms for the problem of multiple fault diagnosis (MFD). The MFD problem is described by a bipartite diagnosis graph (BDG) which consists of a set of components, a ...