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» Selectivity estimation in spatial networks
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MICCAI
2006
Springer
14 years 9 months ago
A Nonparametric Bayesian Approach to Detecting Spatial Activation Patterns in fMRI Data
Traditional techniques for statistical fMRI analysis are often based on thresholding of individual voxel values or averaging voxel values over a region of interest. In this paper w...
Hal S. Stern, Padhraic Smyth, Seyoung Kim
ICDCS
2008
IEEE
14 years 3 months ago
Data Estimation in Sensor Networks Using Physical and Statistical Methodologies
Wireless Sensor Networks (WSNs) are employed in many applications in order to collect data. One key challenge is to minimize energy consumption to prolong network lifetime. A sche...
Yingshu Li, Chunyu Ai, Wiwek P. Deshmukh, Yiwei Wu
MICCAI
2009
Springer
14 years 10 months ago
Tractography-Based Parcellation of the Cortex Using a Spatially-Informed Dimension Reduction of the Connectivity Matrix
Determining cortical functional areas is an important goal for neurosciences and clinical neurosurgery. This paper presents a method for connectivity-based parcellation of the enti...
Cyril Poupon, Denis Rivière, Jean-Francois ...
IPAS
2007
13 years 11 months ago
Color filter array interpolation based on spatial adaptivity
Conventional approach in single-chip digital cameras is a use of color lter arrays (CFA) in order to sample di erent spectral components. Demosaicing algorithms interpolate these ...
Dmitriy Paliy, Radu Ciprian Bilcu, Vladimir Katkov...
CORR
2006
Springer
113views Education» more  CORR 2006»
13 years 8 months ago
Decentralized Maximum Likelihood Estimation for Sensor Networks Composed of Nonlinearly Coupled Dynamical Systems
Abstract--In this paper, we propose a decentralized sensor network scheme capable to reach a globally optimum maximum-likelihood (ML) estimate through self-synchronization of nonli...
Sergio Barbarossa, Gesualdo Scutari