/*! \page page_pfb Polyphase Filterbanks

\section Introduction

Polyphase filterbanks (PFB) are a very powerful set of filtering tools
that can efficiently perform many multi-rate signal processing
tasks. GNU Radio has a set of polyphase filterbank blocks to be used
in all sorts of applications. These blocks and their documentation can
be found in \ref pfb_blk.

\section Usage

See the documentation for the individual blocks for details about what
they can do and how they should be used. Furthermore, there are
examples for these blocks in <b>gnuradio-examples/python/pfb</b>.

The main issue when using the PFB blocks is defining the prototype
filter, which is passed to all of the blocks as a vector of \p
taps. The taps from the prototype filter which get partitioned among
the \p N channels of the channelizer.

An example of creating a set of filter taps for a PFB channelizer is
found on line 49 of <b>gnuradio-examples/python/pfb/channelizer.py</b>
and reproduced below. Notice that the sample rate is the sample rate
at the input to the channelizer while the bandwidth and transition
width are defined for the channel bandwidths. This makes a fairly long
filter that is then split up between the \p N channels of the PFB.

\code
    self._fs = 9000          # input sample rate
    self._M = 9              # Number of channels to channelize

    self._taps = gr.firdes.low_pass_2(1, self._fs, 475.50, 50,
                                      attenuation_dB=100,
				      window=gr.firdes.WIN_BLACKMAN_hARRIS)
\endcode

In this example, the signal into the channelizer is sampled at 9 ksps
(complex, so 9 kHz of bandwidth). The filter uses 9 channels, so each
output channel will have a bandwidth and sample rate of 1 kHz. We want
to pass most of the channel, so we define the channel bandwidth to be
a low pass filter with a bandwidth of 475.5 Hz and a transition
bandwidth of 50 Hz, but we have defined this using a sample rate of
the original 9 kHz. The prototype filter has 819 taps to be divided up
between the 9 channels, so each channel uses 91 taps. This is probably
over-kill for a channelizer, and we could reduce the amount of taps
per channel to a couple of dozen with no ill effects.

The basic rule when defining a set of taps for a PFB block is to think
about the filter running at the highest rate it will see while the
bandwidth is defined for the size of the channels. In the channelizer
case, the highest rate is defined as the rate of the incoming signal,
but in other PFB blocks, this is not so obvious.

Two very useful blocks to use are the arbitrary resampler and the
clock synchronizer (for PAM signals). These PFBs are defined with a
set number of filters based on the fidelity required from them, not
the rate changes. By default, the \p filter_size is set to 32 for
these blocks, which is a reasonable default for most tasks. Because
the PFB uses this number of filters in the filterbank, the maximum
rate of the bank is defined from this (see the theory of a polyphase
interpolator for a justification of this). So the prototype filter is
defined to use a sample rate of \p filter_size times the signal's
sampling rate.

A helpful wrapper for the arbitrary resampler is found in
<b>gnuradio-core/src/python/gnuradio/blks2impl/pfb_arb_resampler.py</b>,
which is exposed in Python as <b>blks2.pfb_arb_resampler_ccf</b> and
<b>blks2.pfb_arb_resampler_fff</b>. This block is set up so that the
user only needs to pass it the real number \p rate as the resampling
rate. With just this information, this hierarchical block
automatically creates a filter that fully passes the signal bandwidth
being resampled but does not pass any out-of-band noise. See the code
for this block for details of how the filter is constructed.

Of course, a user can create his or her own taps and use them in the
arbitrary resampler for more specific requirements. Some of the UHD
examples (<b>gr-uhd/examples</b>) use this ability to create a
received matched filter or channel filter that also resamples the
signal.

\section Examples

The following is an example of the using the channelizer. It creates
the appropriate filter to channelizer 9 channels out of an original
signal that is 9000 Hz wide, so each output channel is now 1000
Hz. The code then plots the PSD of the original signal to see the
signals in the origina spectrum and then makes 9 plots for each of the
channels.

NOTE: you need the Scipy and Matplotlib Python modules installed to
run this example.

\include gnuradio-core/src/examples/pfb/channelize.py

*/