Add lecture

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Blizzard Finnegan 2022-01-13 09:25:15 -05:00
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% File: 13-01-2022.tex
% Created: 07:32:59 Thu, 13 Jan 2022 EST
% Last Change: 07:32:59 Thu, 13 Jan 2022 EST
%
\documentclass[letterpaper]{article}
\usepackage{amsmath}
\usepackage{graphicx}
\usepackage{cancel}
\usepackage{amssymb}
\usepackage{listings}
\usepackage[shortlabels]{enumitem}
\usepackage{lipsum}
\usepackage{soul}
\usepackage{geometry}
\geometry{portrait, margin=1in}
\date{ 2022-01-13 }
\title{%
Statistics\\
\large EEET--425--01: Digital System Processing}
\author{Blizzard MacDougall}
\begin{document}
\maketitle
\pagenumbering{arabic}
SNR (signal to noise ratio) is the mean over the standard deviation.
Alternatively, power of signal over power over noise.
Variance:
\begin{equation}
\hat{\sigma}^2=\frac{1}{N-1}\sum^{N-1}_{i=0}(x_i-\mu)^2
\end{equation}
Standard deviation is the sqrt of the variance.
Power is functionally equivalent to variance.
When sampling a signal, the following is used for calculations:
\begin{equation}
\begin{split}
\hat{\mu}=\frac1N\sum^{N-1}_{i=0}x_i\\
\hat{\sigma}^2=\frac{1}{N-1}\sum^{N-1}_{i=0}(x_i-\hat{\mu})^2
\end{split}
\end{equation}
When you get new samples, you need to remember all the old samples as well.
Variance can also be calculated as:
\begin{equation}
\sigma^2=\frac1{N-1}\left( \sum x^2 - \frac{\left( \sum x\right)^2}{N}\right)
\end{equation}
\end{document}