7.1.txt

written by joshua benker
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7.1: A short introduction to Digital Signal Processing

1) What is the defining property of Gaussian noise?
The defining property is that the probability of the Gaussian Noise is normally distributed. It was named after
the german mathematician Karl Friedrich Gauss. It has a probability density function, short "pdf". The function 
can be described as an exponentiell function whose negative exponent is the variance and the expected value. 
It is normalized by a prefactor so that the content always equals 1. 
(Smith, S., The Scientist and Engineer's Guide to Digital Signal Processing, 1999, Chapter 15, p.178-181)

2) What does a low-pass filter do in general?
A low-pass filter is an filter that transmits only frequencies below a prescribed frequency limit.
It is composed of a selection of adjacent positive points and the output signlas is a weighted average
of many adjacent points from the input signla. The high frequency components will be removed.
digital low-pass filters are used e.g. for noise reduction, wave shaping and signal separation.
(Smith, S., The Scientist and Engineer's Guide to Digital Signal Processing, 1999, Chapter 7, p.128)

3) Is a moving average filter a low-pass or a high-pass filter? Why?
The moving average filter is a more simplier to a low-pass filter, as described by Smith (1999) an 
"exceptionally bad low-pass filter", and it is used for smoothing an array of sampled signal.
The moving average filter takes a number of samples from the input signal at a time and takes the 
average of those to produce a single point in the output signal. This filter is good for time domain 
encoded signals, but in contraire not so good for frequency domain encoded signal.
(Smith, S., The Scientist and Engineer's Guide to Digital Signal Processing, 1999, Chapter 15, p.178-181)