時間領域信号の三次元可視化画像への変換とその応用

抄録

Cognition of the time domain signals has been mostly depended on the experiences of the skillful observers. We have proposed a new methodology in order to carry out for human voice cognition. Since the human voice depends on each of the persons even if the same word pronouncing, then it is essentially accompanying the data based learning process.
To overcome this difficulty, in this paper, we apply the image cognition technology of the human voice to the cognition of magnetic sensor signals. The time domain signals are converted into the three-dimensional image data by means of the modified Lissajous diagram.
Further we have tried to compress the three-dimensional Lissajous diagram by means of the discrete wavelet transform. As the result, it is revealed that the wavelet transform makes it possible to reduce the database quantities.