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COR
2008
116views more  COR 2008»
14 years 10 months ago
Supply disruptions with time-dependent parameters
We consider a firm that faces random demand and receives product from a single supplier who faces random supply. The supplier's availability may be affected by events such as...
Andrew M. Ross, Ying Rong, Lawrence V. Snyder
ICCV
2003
IEEE
16 years 18 days ago
Recognition of Group Activities using Dynamic Probabilistic Networks
Dynamic Probabilistic Networks (DPNs) are exploited for modelling the temporal relationships among a set of different object temporal events in the scene for a coherent and robust...
Shaogang Gong, Tao Xiang
ICIP
2006
IEEE
16 years 10 days ago
A Profile Hidden Markov Model Framework for Modeling and Analysis of Shape
In this paper we propose a new framework for modeling 2D shapes. A shape is first described by a sequence of local features (e.g., curvature) of the shape boundary. The resulting ...
Rui Huang, Vladimir Pavlovic, Dimitris N. Metaxas
ICC
2007
IEEE
135views Communications» more  ICC 2007»
15 years 5 months ago
New Results on Single-Step Power Control System in Finite State Markov Channel: Power Control Error Modelling and Queueing Varia
— The analysis regarding the impact of the single-step power control (SSPC) scheme on the system performance such as bit error rate, packet error rate and queueing variation is h...
Shi-Yong Lee, Min-Kuan Chang
ICIP
2001
IEEE
16 years 8 days 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