Thanks alot Zappedagain
can I look at it in this way:
we have just one analog signal x(t) which is sampled respecting nyquist theorem.then these discrete values enter to the chanel hc(t).
then, we're in the end side of channel. if we look at our output signal in freq. domain: X(f)is convolved with a train of delta dirac signals and then the results multiplied with the Channel freq. response Hc(f).
the frequency shape of Hc(f)is very important in order that we don't face up Aliasing and signal be retreivable.
now, look at it in time domain,
the same sampled signal that has discrete voltages in the time domain enters the channel. the shape of channel in time domain is important in order that we can retrieve these time samples of the original signal.
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Zappedagain, i don't quite understand your point of view.
why are you looking at the input signals to the channel as a random variable and their probability?
even for a deterministic signal, if the channel time-shape is very large, we'll have ISI.
thanks
Pardis