Fitting of uncertain data, that is, fitting of data points that are subject to some error, has important applications for example in statistics and for the evaluation of results from physical experiments. Fitting in these problem domains is usually achieved with polynomial approximation, which involves the minimization of an error at discrete data points. Norms typically used for this minimizat...

A novel approach to estimating sinusoidd parameters of musical tones is presented. The proposed algorithm uses a quadratic polynomial phase sinusoidal model and a global waveform fitting criterion to obtain optimal model parameter estimates.

In this paper, we extend the Maximum Likelihood (ML) training algorithm to the Minimum classificnrtion Emor (MCE) training algorithm for optimal estimation of the state-dependent polynomial coefficients in the trended HMM [2]. The problem of automatic speech recognition is viewed as a discriminative dynamic data-fitting problem, where nlotiue (not absolute) closeness in fitting an array of dyna...