Wavelet Models for Video Time-Series
Abstract
In this work, we tackle the problem of time-series modeling of video traffic. Different from the existing methods which model the time(cid:173) series in the time domain, we model the wavelet coefficients in the wavelet domain. The strength of the wavelet model includes (1) a unified approach to model both the long-range and the short-range dependence in the video traffic simultaneously, (2) a computation(cid:173) ally efficient method on developing the model and generating high quality video traffic, and (3) feasibility of performance analysis us(cid:173) ing the model.
Cite
Text
Ma and Ji. "Wavelet Models for Video Time-Series." Neural Information Processing Systems, 1997.Markdown
[Ma and Ji. "Wavelet Models for Video Time-Series." Neural Information Processing Systems, 1997.](https://mlanthology.org/neurips/1997/ma1997neurips-wavelet/)BibTeX
@inproceedings{ma1997neurips-wavelet,
title = {{Wavelet Models for Video Time-Series}},
author = {Ma, Sheng and Ji, Chuanyi},
booktitle = {Neural Information Processing Systems},
year = {1997},
pages = {915-921},
url = {https://mlanthology.org/neurips/1997/ma1997neurips-wavelet/}
}