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시간 지연을 갖는 쌍전파 신경회로망을 이용한 근전도 신호인식에 관한 연구
권장우,정인길,홍승홍,Kwon, Jangwoo,Jung, Inkil,Hong, Seunghong 대한의용생체공학회 1996 의공학회지 Vol.17 No.3
In this paper a new neural network model, time delayed counterpropagation neural networks (TDCPN) which have high recognition rate and short total learning time, is proposed for electromyogram(EMG) recognition. Signals the proposed model increases the recognition rates after learned the regional temporal correlation of patterns using time delay properties in input layer, and decreases the learning time by using winner-takes-all learning rule. The ouotar learning rule is put at the output layer so that the input pattern is able to map a desired output. We test the performance of this model with EMG signals collected from a normal subject. Experimental results show that the recognition rates of the suggested model is better and the learning time is shorter than those of TDNN and CPN.
AR모델을 이용한 심전도와 맥파의 심박변동 스펙트럼 해석
김낙환,이은실,민홍기,이응혁,홍승홍,Kim NagHwan,Lee EunSil,Min HongKi,Lee EungHyuk,Hong SeungHong 한국융합신호처리학회 2000 융합신호처리학회 논문지 (JISPS) Vol.1 No.1
The analysis of power spectrum based on linear AR model is applied widely to quantize the response of autonomic nerve noninvasively, In this paper, we estimate the power spectrum density for heartrate variability of the electrocadiogram and pulse wave for short term data(less than two minute), The time series of heart rate variability is obtained from the time interval(RRI, PPI) between the feature point of the electrocadiogram and pulse wave for normal person, The generated time series reconstructed into new time series through polynomial interpolation to apply to the AR mode. The power spectrum density for AR model is calculated by Burg algorithm, After applying AR model, the power spectrum density for heart rate variability of the electrocadiogram and the pulse wave is shown smooth spectrum power at the region of low frequence and high frequence, and that the power spectrum density of electrocadiogram and pulse wave has similar form for same subject.