VLSI_Class_Notes_1_Statistical_Analysis_for_ICs-1

VLSI_Class_Notes_1_Statistical_Analysis_for_ICs-1 - EEL...

Info iconThis preview shows pages 1–3. Sign up to view the full content.

View Full Document Right Arrow Icon

Info iconThis preview has intentionally blurred sections. Sign up to view the full version.

View Full DocumentRight Arrow Icon
This is the end of the preview. Sign up to access the rest of the document.

Unformatted text preview: EEL 5322 W.R. Eisenstadt STAT, 1 Page 1 of 3 Statistical Analysis for ICs: Review (hopefully) Arithmetic Mean, μ (measure of tendency) &- = = 1 ) ( 1 N n n x N m Where x (n) is a sampled data set n= 0, 1, 2, 3, & , N-1 Standard Deviation, σ (measure of uncertainty) [ ] &- =- = 1 2 ) ( 1 N n n x N m s Variance, σ² - square of standard deviation For an IC process with many inputs with different standard deviations, total standard deviation, テ Total becomes: Input 1 = テ 1 Input 2 = テ 2 Input n = テ n Total variance, テ ² Total = テ ² 1 + テ ² 2 + & + テ ² n Total Standard Deviation, テ Total 2 2 2 2 1 ... n Total s s s s + + + = For a signal with the DC component subtracted. [ ] &- = = 1 2 ) ( 1 N n n x N RMS Signal EEL 5322 W.R. Eisenstadt STAT, 1 Page 2 of 3 Probabilities and Probability Density Functions Central Limit theorem: Distribution of a set of random variables; statistically independent, becomes large (N>30) tends toward a Gaussian distribution....
View Full Document

This note was uploaded on 10/24/2011 for the course EEE 5322 taught by Professor W.r.eisenstadt during the Fall '10 term at University of Florida.

Page1 / 3

VLSI_Class_Notes_1_Statistical_Analysis_for_ICs-1 - EEL...

This preview shows document pages 1 - 3. Sign up to view the full document.

View Full Document Right Arrow Icon
Ask a homework question - tutors are online