| dc.description.abstract | This paper probes into property of noise and discusses whether its distribution is the ’’normal distribution’’
which is generally the basic assumption of algorithm of classification. And getting noise from it, whether its distribution is independent and identically distributed. If the distribution of noise is normal, the classifications are relatively efficient. In addition, by observing the histogram of noise and its normalization model, we find abnormality, unformly scattering with large percentage near the center. By comparing with noise of other experiments, we conclude that abnormal noise in the histogram may be resulted from the instruments or just the other weak signals received by the electrode .
When observing the representation of noise in the frequency domain, we find irregularity in the frequency domain which causes abnormality in the histogram in the time domain. Moreover, we find the power of noise shows steady wave in the frequency domain. Accordingly, we propose a kind of new filtering method, to make the distribution of noise conform to the normal distribution and make it more independent than the original one. On the other hand, in real nerve signals, the classification will be improved by a fillering based on the fact that the power of noise shows steady wave in the frequency domain. After filtering, the classification is better than that by PCA scattering plot. | en_US |