Estimating the error bound in QOBE Vowel classification

Well documented adaptive properties of quasi-optimal bounding ellipsoid (QOBE) algorithms depend on the choices of error bound. Such dependency becomes particularly noticeable in QOBE linear parameter estimation of speech signals. Vowel classification, for example, would therefore stands to benefit from the efficiency of QOBE algorithms. This paper discusses tradeoffs in error bound estimation and presents related experiments and simulations.