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在readme文件中有：
Compressed Sensing Toolbox for GNU Radio
=========================================
This toolbox enhances GNU Radio with features for compressed sensing.
Compressed Sensing (CS) is a recently popularized methodology to aquire or process signals at sub-Nyquist rate. Compression is implemented by a linear projection. For Cognitive Radio (CR) applications, CS holds the promise of allowing new trade-offs between sampling rate and signal to noise ratio for estimation and detection.
Python usage:
-------------
Run
>>> from gnuradio import gr,cs
to get access to the features.
E.g. cs.circmat_vccb() gives you a processing block which compresses vectors with a circular
matrix.
Specific Documentation:
-----------------------
Can be found in the Doxygen docblocks.
Feature list:
-------------
Compression blocks: Most compression blocks work on vectors, i.e. they take a long
vector and output a shorter one. These blocks are marked with a 'v' in their
type suffix, e.g. circmat_vccb.
The type suffixes are based on the ones in the GNU Radio core, e.g. 'vccf' stands
for complex vector in, complex vector out, float compression matrix.
The 'b' type compression matrices (e.g. vccb) work a bit differently: They actually
take signed chars as compression data. These blocks can be switched to interpret zeros
as -1, which comes in handy when creating pseudorandom 0/1 sequences with shift
registers that should actually be interpreted as -1/1 sequences. Of course, -1/1
sequences can also be directly fed to these blocks, as well as ternary sequences
(-1/0/1).
Roadmap:
--------
In random order:
- Smashed Filters
- Compression on FPGA
有点不太理解啊，我gnuradio装好了的，但就是gr-cs装不上。。
回复 3# dooros
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发表于 2012-04-09 20:23
发表于 2012-04-09 22:19
