Abstract
This paper improves a pattern recognition method for the signals under the noisy environment using method of emphasizing wavelet coefficients for reference clean signal data. If the data is polluted with noise, these signal pattern recognitions are extremely difficult problem. To analyze noise problem, people in general have used the fourier analysis. But the fourier analysis reveals only the frequency information. And the general noise filters reduce specific frequency band contained both noise and signal. It is difficult to eliminate only noise component from a signal containing noise signal. To overcome this difficulty, we applied the wavelet analysis. In this paper, we improve the noisy signal pattern recognition by bringing it close to reference data and noisy input data by modifying the spectrum by using the wavelet transform for reference clean signal data. As a result, noisy signal pattern recognition rate is improved by this method.