State encoding of Hidden Markov linear prediction models

Vikram Krishnamurthy, H. Vincent Poor

Research output: Contribution to journalArticlepeer-review


In this paper, we derive finite-dimensional non-linear filters for optimally reconstructing speech signals in Switched Prediction vocoders, Code Excited Linear Prediction (CELP) and Differential Pulse Code Modulation (DPCM). Our filter is an extension of the Hidden Markov filter.

Original languageEnglish (US)
Pages (from-to)153-157
Number of pages5
JournalJournal of Communications and Networks
Issue number3
StatePublished - Sep 1999

All Science Journal Classification (ASJC) codes

  • Information Systems
  • Computer Networks and Communications


  • Finite dimensional filters
  • Markov jump linear systems
  • Non-linear filtering
  • Speech synthesis
  • State estimation


Dive into the research topics of 'State encoding of Hidden Markov linear prediction models'. Together they form a unique fingerprint.

Cite this