Correlation dimension based lossless compression of EEG signals
作者： N. Sriraam
DOI: 10.1016/J.BSPC.2011.06.007
关键词:
摘要: Abstract Transmission of long duration EEG signals without loss information is essential for telemedicine based applications. In this work, a lossless compression scheme on neural network predictors using the concept correlation dimension (CD) proposed. which are considered as irregular time series chaotic processes can be characterized by non-linear dynamic parameter CD measure among samples. The samples first divided into segments 1 s and each segment, value calculated. Blocks then constructed such that block contains with closer values. By arranging in fashion, accuracy predictor improved it makes use highly correlated As result, magnitude prediction error decreases leading to less number bits transmission. Experiments conducted recorded under different physiological conditions. Different well classical considered. Experimental results show proposed preprocessing improves performance significantly.
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