Title :
The performance of spectral quality measures
Author :
Broersen, Piet M T
Author_Institution :
Dept. of Appl. Phys., Delft Univ. of Technol., Netherlands
fDate :
6/1/2001 12:00:00 AM
Abstract :
Two different classes of quality measures are discussed and compared: absolute and relative measures. The relative class, to which the prediction error belongs, has many different equivalent members, like the spectral distortion and the likelihood ratio. This type of measure is based on time series theory. The prediction error can be written either as a squared error of prediction in the time domain or as a relative error in the frequency domain. It is useful in many applications, especially in comparing models obtained with different estimation algorithms. It is compared to some measures that are absolute in the frequency domain. To that class belongs the integrated squared difference between spectra, that gives equal weights to all frequencies. Another measure is based on the squared difference between impulse responses. The absolute class has only a few practical applications, mainly in speech
Keywords :
autoregressive processes; maximum likelihood estimation; mean square error methods; modelling; prediction theory; spectral analysis; time series; transient response; absolute measures; autoregressive models; equal weights; equivalent members; estimation algorithms; frequency domain; integrated squared difference between spectra; likelihood ratio; models comparison; performance comparison; prediction error; relative error; relative measures; spectral distortion; spectral quality measures; squared difference between impulse responses; squared error; time domain; time series theory; Accuracy; Cepstrum; Distortion measurement; Frequency domain analysis; Frequency estimation; Frequency measurement; Polynomials; Predictive models; Speech processing; Time measurement;
Journal_Title :
Instrumentation and Measurement, IEEE Transactions on