Objective: To study extracellular multi-neuron activity in the nervous system based on wavelet-fractal technique. Methods: The wavelet transform was employed to decompose the original signal and obtain 4 sub-patterns....Objective: To study extracellular multi-neuron activity in the nervous system based on wavelet-fractal technique. Methods: The wavelet transform was employed to decompose the original signal and obtain 4 sub-patterns. The dividing fractal dimensions of these sub-patterns were computed. A knn-classier was used to classify feature vectors. Results: Not all the elements in feature vector DimDC were very powerful for this pattern recognition problem through the empirical study of noise signals. The most effective feature vector was defined as DimDC= (d3:d4) above. Conclusion:Wavelet fractal algorithm has high accuracy and provides a powerful tool for clinical application.展开更多
Recently,real-time processing systems for bio-signal of the muscles generated by the movement of the user have been developed.Finite impulse response(FIR)filter for bio-signal processing in bio-signal process systems ...Recently,real-time processing systems for bio-signal of the muscles generated by the movement of the user have been developed.Finite impulse response(FIR)filter for bio-signal processing in bio-signal process systems is composed of multiple multiplier and adder of high-area.This makes the chip area increase significantly.To solve this problem,a low-area digital FIR filter is proposed in this paper,which can reduce the chip area.展开更多
基金Supported by the National Natural Science Foundation of China (No. 60371034)
文摘Objective: To study extracellular multi-neuron activity in the nervous system based on wavelet-fractal technique. Methods: The wavelet transform was employed to decompose the original signal and obtain 4 sub-patterns. The dividing fractal dimensions of these sub-patterns were computed. A knn-classier was used to classify feature vectors. Results: Not all the elements in feature vector DimDC were very powerful for this pattern recognition problem through the empirical study of noise signals. The most effective feature vector was defined as DimDC= (d3:d4) above. Conclusion:Wavelet fractal algorithm has high accuracy and provides a powerful tool for clinical application.
基金The MKE(the Ministry of Knowledge Economy),Korea,under the ITRC(Information Technology Research Center)support program supervised by the NIPA(National IT Industry Promotion Agency) (NIPA-2012-H0301-12-2006)the Seoul Metropolitan Government,under the Seoul R & BD Program supervised by Seoul Business Agency(ST110039)
文摘Recently,real-time processing systems for bio-signal of the muscles generated by the movement of the user have been developed.Finite impulse response(FIR)filter for bio-signal processing in bio-signal process systems is composed of multiple multiplier and adder of high-area.This makes the chip area increase significantly.To solve this problem,a low-area digital FIR filter is proposed in this paper,which can reduce the chip area.
