The signal
is bandlimited to 4 kHz. We want to sample it,
but it has been subjected to various signal processingmanipulations.
What sampling frequency (if any works) can be used
to sample the result of passing
through an RC highpass filter with
and
?
What sampling frequency (if any works) can be used to
sample the
derivative of
?
The signal
has been modulated by an 8 kHz
sinusoid having an unknown phase: the resultingsignal is
, with
and
Can the modulated signal be sampled so that the
original signal can be recovered from
the modulated signal regardless of the phase value
? If so, show how and
find the smallest sampling rate that can be used; if not,show why not.
Non-standard sampling
Using the properties of the Fourier series can ease
finding a signal's spectrum.
Suppose a signal
is periodic with period
. If
represents the signal's Fourier series
coefficients, what are the Fourier seriescoefficients of
?
Find the Fourier series of the signal
shown in
[link] .
Suppose this signal is used to sample a signal
bandlimited to
. Find an expression for and sketch the spectrum
of the sampled signal.
Does aliasing occur? If so, can a change in sampling
rate prevent aliasing;if not, show how the signal can be
recovered from these samples.
A different sampling scheme
A signal processing engineer from Texas
A&M claims to have developed an improved sampling
scheme. He multiplies the bandlimited signal by the
depicted periodic pulse signal to perform sampling (
[link] ).
Find the Fourier spectrum of this signal.
Will this scheme work? If so, how should
be related to the signal's bandwidth?
If not, why not?
Bandpass sampling
The signal
has the indicated spectrum.
What is the minimum sampling rate for this signal
suggested by the Sampling Theorem?
Because of the particular structure of this
spectrum, one wonders whether a lower sampling ratecould be used. Show that this is indeed the case, and
find the system that reconstructs
from its samples.
Sampling signals
If a signal is bandlimited to
Hz, we can sample it at
any rate
and recover the waveform exactly. This statement of the
Sampling Theorem can be taken to mean that allinformation about the original signal can be extracted
from the samples. While true in principle, you do haveto be careful how you do so. In addition to the rms
value of a signal, an important aspect of a signal isits peak value, which equals
.
Let
be a sinusoid having frequency
Hz. If we sample it
at precisely the Nyquist rate, how accurately do thesamples convey the sinusoid's amplitude? In other
words, find the worst case example.
How fast would you need to sample for the
amplitude estimate to be within 5% of the truevalue?
Another issue in sampling is the inherent amplitude
quantization produced by A/D converters. Assume themaximum voltage allowed by the converter is
volts and that it quantizes amplitudes to
bits.
We can express the quantized sample
as
, where
represents the quantization error at the
sample. Assuming the converter rounds, how large is
maximum quantization error?
We can
describe the quantization error as noise, with apower proportional to the square of the maximum
error. What is the signal-to-noise ratio of thequantization error for a full-range sinusoid?
Express your result in decibels.