Detail publikace

Method for Real-time Signal Processing via Wavelet Transform

Originální název

Method for Real-time Signal Processing via Wavelet Transform

Anglický název

Method for Real-time Signal Processing via Wavelet Transform

Jazyk

en

Originální abstrakt

The new method of segmented wavelet transform (SegWT) makes it possible to compute the discrete-time wavelet transform of a signal segment-by-segment. This means that the method could be utilized for wavelet-type processing of a signal in ``real time'', or in case we need to process a long signal (not necessarily in real time), but there is insufficient computational memory capacity for it (for example in the signal processors). Then it is possible to process the signal part-by-part with low memory costs by the new method. The method is suitable also for the speech processing, e.g. denoising the speech signal via thresholding the wavelet coefficients or speech coding. In the paper, the principle of the segmented forward wavelet transform is described.

Anglický abstrakt

The new method of segmented wavelet transform (SegWT) makes it possible to compute the discrete-time wavelet transform of a signal segment-by-segment. This means that the method could be utilized for wavelet-type processing of a signal in ``real time'', or in case we need to process a long signal (not necessarily in real time), but there is insufficient computational memory capacity for it (for example in the signal processors). Then it is possible to process the signal part-by-part with low memory costs by the new method. The method is suitable also for the speech processing, e.g. denoising the speech signal via thresholding the wavelet coefficients or speech coding. In the paper, the principle of the segmented forward wavelet transform is described.

Dokumenty

BibTex


@inproceedings{BUT15973,
  author="Pavel {Rajmic}",
  title="Method for Real-time Signal Processing via Wavelet Transform",
  annote="The new method of segmented wavelet transform (SegWT) makes it possible to compute the
discrete-time wavelet transform of a signal segment-by-segment. This means that the
method could be utilized for wavelet-type processing of a signal in ``real time'', or in case we need to process a long signal (not necessarily in real time), but there is insufficient computational memory capacity for it (for example in the signal processors). Then it is possible to process the signal part-by-part with low memory costs by the new
method.
The method is suitable also for the speech processing, e.g. denoising the speech signal
via thresholding the wavelet coefficients or speech coding.
In the paper, the principle of the segmented forward wavelet transform is described.",
  address="Escola Universitaria Politecnica de Mataró",
  booktitle="Proceedings of the 3th International Conference on Non-Linear Speech Processing",
  chapter="15973",
  institution="Escola Universitaria Politecnica de Mataró",
  year="2005",
  month="april",
  pages="214",
  publisher="Escola Universitaria Politecnica de Mataró",
  type="conference paper"
}