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Am reading Rick Lyons - Understanding DSP book about Sampling. I have few doubts related to this chapter.

  1. what is the difference between Bandpass Signal and a Passband Signal ?
  2. Can somebody give an example for a Bandpass system which produces Bandpass signal as output !
  3. When it comes to Baseband Sampling ( Low pass Sampling ) sampling theorem states that " Fs > twice the Highest frequency Component" and for Bandpass Sampling, sampling theorem says Fs > twice the Bandwidth of the signal. why two different sampling statements for the same signal of B hertz.

I understand in Bandpass sampling if I sample at the rate of twice the highest frequency component, then it'll be oversampling.

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  • $\begingroup$ I don't have the book in front of me, but typicaly the distinction is between bandpass signals and baseband signals. Baseband signals are centered at zero frequency (i.e. the base of the band). A bandpass signal is one that is centered at some nonzero center (or carrier) frequency. $\endgroup$ – Jason R Mar 20 '13 at 13:57
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what is the difference between Bandpass Signal and a Passband Signal ?

There are several kinds of filters, with names that describe their function:

For all of these filters, different frequencies are either passed or stopped by the filter, giving them their name. You can then talk about the regions that are passed or stopped using the words:

For instance:

  • 100 Hz is in the passband of a 200 Hz lowpass filter, while 300 Hz is in the stopband.
  • 100 Hz is in the stopband of a 200 Hz highpass filter.
  • 200 Hz is in the passband of a 100-300 Hz bandpass filter, while 50 Hz is in the stopband.
  • All frequencies are in the passband of an all-pass filter. All-pass filters have no stopband.

A "passband signal" is a signal that falls into the passband of a given filter. What that means depends on the type of filter you're talking about.

A "bandpass signal" is a signal that has passed through a band-pass filter.

Can somebody give an example for a Bandpass system which produces Bandpass signal as output !

All of them!

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  1. A PassBand is the Band that can be passed through a BandPass filter, or for that matter, any filter. In other words, the filter is a Bandpass, what signal passes through is a Passband.
  2. The classic is a high pass and low pass together. For instance, a capacitor, inductor, and resistor in series is an example of a bandpass filter. Digitally, you combine a high pass and a low pass filter together.
  3. Essentially, if you are limited to a small region, you can infer what frequency you are limited to. The classic example is Nf->2*Nf. The frequencies reported at 0 is 2*Nf, the frequency reported at Nf is actually NF, and continue the pattern for the rest. This only works when you are guaranteed to only have frequencies in the particular band.
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    $\begingroup$ lowpass and highpass filters have passbands, too. maybe that helps explain $\endgroup$ – endolith Mar 20 '13 at 15:19
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what is the difference between Bandpass Signal and a Passband Signal ?

I would normally refer to a band-limited signal. IE a signal which is limited in bandwidth to some degree. All real-world signals are "band-limited signals". I have looked in the book for a reference to bandpass signals and can't see one.

I would call a passband signal "a signal which falls within the passband of a filter" and hence passes through it more-or-less unmodified.

Can somebody give an example for a Bandpass system which produces Bandpass signal as output !

I would expect any bandpass system will produce a bandpass signal.

When it comes to Baseband Sampling ( Low pass Sampling ) sampling theorem states that " Fs > twice the Highest frequency Component" and for Bandpass Sampling, sampling theorem says Fs > twice the Bandwidth of the signal. why two different sampling statements for the same signal of B hertz.

The sampling theorem really says the latter ($Fs > 2*bandwidth$) - usually sampling is done at the baseband, so it's simpler to talk in terms of the highest frequency component, but it's actually the same thing when the lowest frequency component is at or very near DC.

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Q3 When it comes to Baseband Sampling ( Low pass Sampling ) sampling theorem states that " Fs > twice the Highest frequency Component" and for Bandpass Sampling, sampling theorem says Fs > twice the Bandwidth of the signal. why two different sampling statements for the same signal of B hertz.

Both statements are same, how? highest frequency of baseband signal defines the bandwidth of that signal because signal starts form zero frequency (bandwidth= highest frequency-zero =highest frequency ) so both are same things in Baseband Sampling ( Low pass Sampling ) sampling theorem, either you say Fs>twice the Highest frequency Component or Fs > twice the Bandwidth of the signal.

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  • $\begingroup$ Aakash, FYI the highest frequency of a baseband signal of 5 MHz is 2.5 MHz, so sampling rate $$ f_s > 2 * 2.5 = 5MHz $$ And when it comes to bandpass signal, $$ f_s = 2 * 5 MHz = 10 MHz $$ [twice the BW], or more precisely sampling rate for bandpass signals will be within $$ (2f_c-B)/m >= f_s >= (2f_c+B)/m $$ $\endgroup$ – rajez79 Oct 21 '13 at 10:28
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Band pass signals basically generated from Band pass filters.In a modulation technique usually, the transmitted signals are bandpass signal.Bandpass filters are widely used in wireless transmitters and receivers. The main function of such a filter in a transmitter is to limit the bandwidth of the output signal to the band allocated for the transmission. This prevents the transmitter from interfering with other stations. In a receiver, a bandpass filter allows signals within a selected range of frequencies to be heard or decoded, while preventing signals at unwanted frequencies from getting through. A bandpass filter also optimizes the signal-to-noise ratio and sensitivity of a receiver.

In both transmitting and receiving applications, well-designed bandpass filters, having the optimum bandwidth for the mode and speed of communication being used, maximize the number of signal transmitters that can exist in a system, while minimizing the interference or competition among signals.

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