Mean Squared Error Quantizer
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Please help to improve this article by introducing more precise citations. (August 2016) (Learn how and when to remove this template message) Mean square quantization error (MSQE) is a figure of merit for quantization error formula the process of analog to digital conversion. In this conversion process, analog signals
Uniform Quantization
in a continuous range of values are converted to a discrete set of values by comparing them with a sequence
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of thresholds. The quantization error of a signal is the difference between the original continuous value and its discretization, and the mean square quantization error (given some probability distribution on the input values)
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is the expected value of the square of the quantization errors. Mathematically, suppose that the lower threshold for inputs that generate the quantized value q i {\displaystyle q_{i}} is t i − 1 {\displaystyle t_{i-1}} , that the upper threshold is t i {\displaystyle t_{i}} , that there are k {\displaystyle k} levels of quantization, and that the probability density function for the input analog values is mean square quantization error formula p ( x ) {\displaystyle p(x)} . Let x ^ {\displaystyle {\hat {x}}} denote the quantized value corresponding to an input x {\displaystyle x} ; that is, x ^ {\displaystyle {\hat {x}}} is the value q i {\displaystyle q_{i}} for which t i − 1 ≤ x < t i {\displaystyle t_{i}-1\leq x toolboxes, and other File Exchange content using Add-On Explorer in MATLAB. » Watch video Highlights from Quantizers Gamma1aCCDFCalculate the uniform quantization pdf integral of a one-sided generalized gamma probability Gamma2aCCDFThis function calculates difference between uniform and nonuniform quantization the complementary cumulative probability GammaGenPDFReturn function handles to routines to calculate the area, mean, GammaPDFReturn quantization error definition function handles to routines to calculate the area, mean, GaussPDFReturn function handles to routines to calculate the area, mean, and LaplacePDFReturn function handles to routines https://en.wikipedia.org/wiki/Mean_square_quantization_error to calculate the area, mean, and LogGammaCalculate the log-gamma function PDFFnReturn pointers to functions to calculate functions of the PDF QuantQuantize a vector of samples QuantALawTables()This routine returns quantization tables for a 256 level segmented A-law QuantEntropyCalculate the entropy for a quantizer QuantLloydIterate to find the output levels for a minimum https://www.mathworks.com/matlabcentral/fileexchange/24333-quantizers/content/Quantizer/QuantMSE.m mean square error QuantMSECalculate the mean-square quantization error QuantMuLawTables()This routine returns quantization tables for a 256 level segmented mu-law QuantOptFind a non-uniform minimum mean square error quantizer. QuantRefineIterate to find the output levels for a MMSE quantizer. QuantSNRCalculate the SNR (dB) for a quantizer defined by a table for a QuantUnifFind a uniform minimum mean square error quantizer. SinePDFReturn function handles to routines to calculate the area, mean, and TabulatedPDFReturn function handles to routines to calculate the area, mean, and TestPDFUse two different methods to calculate each of the following UniformPDFReturn function handles to routines to calculate the area, mean, and lin2pcma(x,m,s) pcma2lin(p,m,s) tGammaCCDF tLogGamma tLogQuantTest Quant for A or mu-law quantizer tables tQuantOpt tQuantUnif View all files Join the 15-year community celebration. Play games and win prizes! » Learn more Quantizers by Peter Kabal Peter Kabal (view profile) 9 files 69 downloads 4.83333 02 Jun 2009 (Updated be down. Please try the request again. Your cache administrator is webmaster. Generated Thu, 20 Oct 2016 11:14:31 GMT by s_wx1085 (squid/3.5.20)