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» Evolving Artificial Neural Networks that Develop in Time
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IJCNN
2008
IEEE
15 years 4 months ago
Kernel methods for fMRI pattern prediction
Abstract— In this paper, we present an effective computational approach for learning patterns of brain activity from the fMRI data. The procedure involved correcting motion artif...
Yizhao Ni, Carlton Chu, Craig J. Saunders, John As...
IJCNN
2008
IEEE
15 years 4 months ago
Multifractal feature vectors for Brain-Computer interfaces
—This article introduces a new feature vector extraction for EEG signals using multifractal analysis. The validity of the approach is asserted on real data sets from the BCI comp...
Nicolas Brodu
BMCBI
2008
136views more  BMCBI 2008»
14 years 9 months ago
A comparison of machine learning algorithms for chemical toxicity classification using a simulated multi-scale data model
Background: Bioactivity profiling using high-throughput in vitro assays can reduce the cost and time required for toxicological screening of environmental chemicals and can also r...
Richard Judson, Fathi Elloumi, R. Woodrow Setzer, ...
ISNN
2009
Springer
15 years 4 months ago
Nonlinear Component Analysis for Large-Scale Data Set Using Fixed-Point Algorithm
Abstract. Nonlinear component analysis is a popular nonlinear feature extraction method. It generally uses eigen-decomposition technique to extract the principal components. But th...
Weiya Shi, Yue-Fei Guo
ROBIO
2006
IEEE
153views Robotics» more  ROBIO 2006»
15 years 3 months ago
GA-based Feature Subset Selection for Myoelectric Classification
– This paper presents an ongoing investigation to select optimal subset of features from set of well-known myoelectric signals (MES) features in time and frequency domains. Four ...
Mohammadreza Asghari Oskoei, Huosheng Hu