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» Input Modeling Using Quantile Statistical Methods
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MICCAI
2005
Springer
14 years 8 months ago
MRI Tissue Classification with Neighborhood Statistics: A Nonparametric, Entropy-Minimizing Approach
We introduce a novel approach for magnetic resonance image (MRI) brain tissue classification by learning image neighborhood statistics from noisy input data using nonparametric den...
Tolga Tasdizen, Suyash P. Awate, Ross T. Whitaker,...
BMCBI
2008
135views more  BMCBI 2008»
13 years 7 months ago
Using Generalized Procrustes Analysis (GPA) for normalization of cDNA microarray data
Background: Normalization is essential in dual-labelled microarray data analysis to remove nonbiological variations and systematic biases. Many normalization methods have been use...
Huiling Xiong, Dapeng Zhang, Christopher J. Martyn...
IPPS
2006
IEEE
14 years 1 months ago
On the impact of data input sets on statistical compiler tuning
In recent years, several approaches have been proposed to use profile information in compiler optimization. This profile information can be used at the source level to guide loo...
Masayo Haneda, Peter M. W. Knijnenburg, Harry A. G...
DATE
2007
IEEE
118views Hardware» more  DATE 2007»
14 years 1 months ago
Statistical model order reduction for interconnect circuits considering spatial correlations
In this paper, we propose a novel statistical model order reduction technique, called statistical spectrum model order reduction (SSMOR) method, which considers both intra-die and...
Jeffrey Fan, Ning Mi, Sheldon X.-D. Tan, Yici Cai,...
ISCAS
2007
IEEE
117views Hardware» more  ISCAS 2007»
14 years 1 months ago
Quantifying Input and Output Spike Statistics of a Winner-Take-All Network in a Vision System
— Event-driven spike-based processing systems offer new possibilities for real-time vision. Signals are encoded asynchronously in time thus preserving the time information of the...
Matthias Oster, Rodney J. Douglas, Shih-Chii Liu