Hybrid Fractal-Wavelet Method for Multi-Channel EEG Signal Compression

作者：Saeedi Jamal^*; Faez Karim; Moradi Mohammad Hassan

来源：Circuits, Systems, and Signal Processing, 2014, 33(8): 2583-2604.

DOI：10.1007/s00034-014-9764-y

• Electroencephalograms
• Compression
• Fractal coding
• Wavelet-based coding
• Multi-objective genetic optimization

In this paper, a hybrid method is proposed for multi-channel electroencephalograms (EEG) signal compression. This new method takes advantage of two different compression techniques: fractal and wavelet-based coding. First, an effective decorrelation is performed through the principal component analysis of different channels to efficiently compress the multi-channel EEG data. Then, the decorrelated EEG signal is decomposed using wavelet packet transform (WPT). Finally, fractal encoding is applied to the low frequency coefficients of WPT, and a modified wavelet-based coding is used for coding the remaining high frequency coefficients. This new method provides improved compression results as compared to the wavelet and fractal compression methods.

• 出版日期2014-8