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» Hidden Markov Models with Multiple Observation Processes
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WIAMIS
2009
IEEE
14 years 2 months ago
Archive film defect detection based on a hidden Markov model
We propose a novel statistical approach to detect defects in digitized archive film by using temporal information across a number of frames modeled with an HMM. The HMM is traine...
Xiaosong Wang, Majid Mirmehdi
CORR
2010
Springer
147views Education» more  CORR 2010»
13 years 7 months ago
High-Rate Quantization for the Neyman-Pearson Detection of Hidden Markov Processes
This paper investigates the decentralized detection of Hidden Markov Processes using the NeymanPearson test. We consider a network formed by a large number of distributed sensors....
Joffrey Villard, Pascal Bianchi, Eric Moulines, Pa...
DATE
2008
IEEE
136views Hardware» more  DATE 2008»
14 years 1 months ago
A Framework of Stochastic Power Management Using Hidden Markov Model
- The effectiveness of stochastic power management relies on the accurate system and workload model and effective policy optimization. Workload modeling is a machine learning proce...
Ying Tan, Qinru Qiu
ECML
2005
Springer
14 years 28 days ago
Using Rewards for Belief State Updates in Partially Observable Markov Decision Processes
Partially Observable Markov Decision Processes (POMDP) provide a standard framework for sequential decision making in stochastic environments. In this setting, an agent takes actio...
Masoumeh T. Izadi, Doina Precup
ICIP
2001
IEEE
14 years 9 months ago
EM algorithms of Gaussian mixture model and hidden Markov model
The HMM (Hidden Markov Model) is a probabilistic model of the joint probability of a collection of random variables with both observations and states. The GMM (Gaussian Mixture Mo...
Guorong Xuan, Wei Zhang, Peiqi Chai