Yes Gibbs phenomenon becomes constraining when we are
analysing signals containing frequency tones quite close to
each other. If the side lobes of the windowing function are
significant then it leads to energy leakages between the
frequency bins/sub-bands. Thus very close lying frenecy
tones gets their magnitudes smeared up in the process.
Anti aliasing filter reduces errors due to aliasing. If a
signal is sampled at 8 kS/S, the max frequency of the input
should be 4 kHz. Otherwise, aliasing errors will result.
Typically a 3.4kHz will have an image of 4.6 khz, and one
uses a sharp cut off filter with gain of about 1 at 3.4kHz
and gain of about 0.01 at 4.6 kHz to effectively guard
against aliasing. Thus one does not quite choose max
frequency as simply fs/2 where fs is sampling frequency.
One has to have a guard band of about 10% of this fmax, and
chooses max signal frequency as 0.9*fs/2
A fourth order Butterworth filter can be made as cascade of
two seond order LP filters with zeta of 0.924 and 0.383.
One can use a bilinear transformation approach for
realising second order LP filters. Using this technique
described well in many texts, one can make two second order
LP filters and cascade them.
Before reading the data if you are giving the stop bit then
the communication is stopped.so after sending the data you
will give the stop bit.
Dirac delta is a continuous time function with unit area and
infinite amplitude at t=0.
the fourier transform of dirac delta is 1.
using dirac delta as an input to the system, we can get the
system respnose. it is used to study the behavior of the
circuit.
we can use this system behavior to find the output for any
input.
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