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» A Sequential Monte Carlo Method for Motif Discovery
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VLSISP
2002
123views more  VLSISP 2002»
13 years 8 months ago
Monte Carlo Bayesian Signal Processing for Wireless Communications
Abstract. Many statistical signal processing problems found in wireless communications involves making inference about the transmitted information data based on the received signal...
Xiaodong Wang, Rong Chen, Jun S. Liu
BMCBI
2005
201views more  BMCBI 2005»
13 years 9 months ago
Principal component analysis for predicting transcription-factor binding motifs from array-derived data
Background: The responses to interleukin 1 (IL-1) in human chondrocytes constitute a complex regulatory mechanism, where multiple transcription factors interact combinatorially to...
Yunlong Liu, Matthew P. Vincenti, Hiroki Yokota
WSC
2008
13 years 11 months ago
A particle filtering framework for randomized optimization algorithms
We propose a framework for optimization problems based on particle filtering (also called Sequential Monte Carlo method). This framework unifies and provides new insight into rand...
Enlu Zhou, Michael C. Fu, Steven I. Marcus
ICPR
2004
IEEE
14 years 10 months ago
Articulate Hand Motion Capturing Based on a Monte Carlo Nelder-Mead Simplex Tracker
This paper presents an algorithm for tracking the articulate hand motion in monocular video sequences. The task is challenging due to the high degrees of freedom involved in the h...
John Lin, Thomas S. Huang, Ying Wu
BMCBI
2007
141views more  BMCBI 2007»
13 years 9 months ago
HeliCis: a DNA motif discovery tool for colocalized motif pairs with periodic spacing
Background: Correct temporal and spatial gene expression during metazoan development relies on combinatorial interactions between different transcription factors. As a consequence...
Erik Larsson, Per Lindahl, Petter Mostad