The Marginal Enumeration Bayesian Cramer-Rao Bound for Jump Markov Systems

Download
2014-04-01
FRITSCHE, Carsten
Orguner, Umut
Svensson, Lennart
Gustafsson, Fredrik
A marginal version of the enumeration Bayesian Cramer-Rao Bound (EBCRB) for jump Markov systems is proposed. It is shown that the proposed bound is at least as tight as EBCRB and the improvement stems from better handling of the nonlinearities. The new bound is illustrated to yield tighter results than BCRB and EBCRB on a benchmark example.
IEEE SIGNAL PROCESSING LETTERS

Suggestions

MARGINAL BAYESIAN BHATTACHARYYA BOUNDS FOR DISCRETE-TIME FILTERING
Fritsche, Carsten; Orguner, Umut; Özkan, Emre; Gustafsson, Fredrik (2018-04-20)
In this paper, marginal versions of the Bayesian Bhattacharyya lower bound (BBLB), which is a tighter alternative to the classical Bayesian Cramer-Rao bound, for discrete-time filtering are proposed. Expressions for the second and third-order marginal BBLBs are obtained and it is shown how these can be approximately calculated using particle filtering. A simulation example shows that the proposed bounds predict the achievable performance of the filtering algorithms better.
Maximum likelihood estimation of transition probabilities of jump Markov linear systems
Orguner, Umut (Institute of Electrical and Electronics Engineers (IEEE), 2008-10-01)
This paper describes an online maximum likelihood estimator for the transition probabilities associated with a jump Markov linear system (JMLS). The maximum likelihood estimator is derived using the reference probability method, which exploits an hypothetical probability measure to find recursions for complex expectations. Expectation maximization (EM) procedure is utilized for maximizing the likelihood function. In order to avoid the exponential increase in the number of statistics of the optimal EM algori...
The limit of sum of Markov Bernoulli variables in system reliability evaluation
Şahinoğlu, Mehmet (Institute of Electrical and Electronics Engineers (IEEE), 1990-4)
For 2-state maintainable and repairable systems modeled by nonstationary Markov chains, a limiting compound Poisson distribution is derived for the sum of Markov Bernoulli random variables. The result is useful for estimating the distribution of the sum of negative-margin hours in a boundary-crossing scenario involving any physical system with interarrival times of system failures that are negative-exponentially distributed, where the positive- and negative-margin states denote desirable and undesirable ope...
A new sure-success generalization of Grover iteration and its application to weight decision problem of Boolean functions
Uyanik, K.; Turgut, Sadi (Springer Science and Business Media LLC, 2013-11-01)
In two recent papers, a sure-success version of the Grover iteration has been applied to solve the weight decision problem of a Boolean function and it is shown that it is quadratically faster than any classical algorithm (Braunstein et al. in J Phys A Math Theor 40:8441, 2007; Choi and Braunstein in Quantum Inf Process 10:177, 2011). In this paper, a new approach is proposed to generalize the Grover's iteration so that it becomes exact and its application to the same problem is studied. The regime where a ...
The Feynman path integral quantization of constrained systems
Muslih, S; Guler, Y (1997-01-01)
The Feynman path integral for constrained systems is constructed using the canonical formalism introduced by Guler. This approach is applied to a free relativistic particle and Christ-Lee model.
Citation Formats
C. FRITSCHE, U. Orguner, L. Svensson, and F. Gustafsson, “The Marginal Enumeration Bayesian Cramer-Rao Bound for Jump Markov Systems,” IEEE SIGNAL PROCESSING LETTERS, pp. 464–468, 2014, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/32845.