Title :
Almost uniformity of quantization errors
Author :
Kushner, H.B. ; Meisner, M. ; Levy, A.V.
Author_Institution :
Div. of Stat. Sci. & Epidemiology, Nathan S. Kline Inst. for Psychiatric Res., Orangeburg, NY, USA
fDate :
8/1/1991 12:00:00 AM
Abstract :
A short alternative derivation of the Fourier series representation of the density of the quantization error is given. The quantization error for the general Gaussian signal, N(μ,σ2 ), is considered and is analytically shown to be almost uniform for σ/Δ>1 where Δ is the quantization step. The problem of estimating μ by quantized observations is considered. A class of distributions with almost uniform quantization error densities is introduced. Particular distributions in this class are the general Gaussian distribution, the gamma distribution, and the Cauchy distribution. A general class of signals and a second class of densities are shown to have almost uniform error densities. The general bivariate Gaussian distribution and certain kinds of multivariate signals have almost uniform quantization errors
Keywords :
analogue-digital conversion; error analysis; probability; random processes; series (mathematics); signal processing; A/D conversion; Cauchy distribution; EEG; Fourier series; Gaussian signal; Poisson summation formula; brain medical imaging; density; gamma distribution; general bivariate Gaussian distribution; multivariate signals; positron emission tomography; quantization errors; signal processing; Biomedical imaging; Computer errors; Fourier series; Gaussian distribution; Positron emission tomography; Psychiatry; Psychology; Quantization; Signal analysis; Sufficient conditions;
Journal_Title :
Instrumentation and Measurement, IEEE Transactions on