Recursively indexed vector quantization of non stationary sources

Ali G. Al-Araj, Khalid Sayood

Research output: Contribution to journalConference articlepeer-review


A recursively indexed vector quantizer is presented. It has the following properties: simple to implement with low computational overhead, it is adaptive and is well suited for applications where the source is non-stationary, the output rate can be easily changed making it suitable for applications requiring rate control, and the input vectors can be quantized. The algorithms have been tested on a number of synthetic hidden Markov sources and on a video sequence and results of both tests compare favorably with existing results in the literature.

Original languageEnglish (US)
Pages (from-to)450
Number of pages1
JournalData Compression Conference Proceedings
StatePublished - 1995
EventProceedings of the 5th Data Compression Conference - Snowbird, UT, USA
Duration: Mar 28 1995Mar 30 1995

ASJC Scopus subject areas

  • Computer Networks and Communications


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