Sequential feature extraction for waveform recognition

WJ STEINGRANT WJ, Sik-Sang Yau

Research output: Chapter in Book/Report/Conference proceedingChapter

1 Scopus citations

Abstract

A means of feature extraction and recognition for waveforms is developed and applied to speech recognition. The concept of sequential feature extraction is formalized and a performance criterion for the resulting extraction is developed. An unsupervised learning algorithm, which will optimize this structure with respect to the performance criterion, is presented. This algorithm, which can be applied to waveform recognition as well as vector recognition, represents an improvement over existing clustering algorithms in many respects. This method will allow unbounded stringsof sample patterns for learning. The samples are presented to the algorithm one at a time so that the storage of large numbers of patterns is unnecessary. The assumption of known probability measures is not made.

Original languageEnglish (US)
Title of host publicationUnknown Host Publication Title
Pages65-76
Number of pages12
Volume36
StatePublished - 1970
Externally publishedYes
EventAFIPS Conf Proc, Spring Jt Comput Conf - Atlantic City, NJ
Duration: May 5 1970May 7 1970

Other

OtherAFIPS Conf Proc, Spring Jt Comput Conf
CityAtlantic City, NJ
Period5/5/705/7/70

ASJC Scopus subject areas

  • Engineering(all)

Fingerprint Dive into the research topics of 'Sequential feature extraction for waveform recognition'. Together they form a unique fingerprint.

  • Cite this

    STEINGRANT WJ, WJ., & Yau, S-S. (1970). Sequential feature extraction for waveform recognition. In Unknown Host Publication Title (Vol. 36, pp. 65-76)