Honored Contributor
Honored ContributorIf you look at Dave's posts after mine, you will see very good description of both noise and dc bias for various truncation algorithms. The case of direct truncation leads to truncation error of up to 1 LSB. Other cases lead to 0.5 LSB error. The actual error power will then depend on probaility issues and can be modelled same as quantisation noise of ADC sampling.
--- Quote Start --- http://www.ovro.caltech.edu/~dwh/correlator/pdf/esc-100paper_hawkins.pdf (http://www.ovro.caltech.edu/%7edwh/correlator/pdf/esc-100paper_hawkins.pdf) http://www.ovro.caltech.edu/~dwh/correlator/pdf/esc-100slides_hawkins.pdf (http://www.ovro.caltech.edu/%7edwh/correlator/pdf/esc-100slides_hawkins.pdf) Look at p40 and p41 of the slides for examples of truncation noise and the different rounding methods available in MATLAB. The figures show the bias involved in all methods; and that convergent is the rounding method to select. --- Quote End ---
