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Author Topic: FLDIGI: two new experimental features to improve CW detection and decoding  (Read 1028 times)
AG1LE
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« on: May 13, 2012, 10:30:51 PM »

I have implemented two new experimental features to improve CW detection and decoding capabilities in FLDIGI softare.

1) Matched Filter  feature improves signal-to-noise making barely audible morse code detection  to work better in FLDIGI  CW mode.

2) Self Organized Map feature is using an artificial neural network algorithm from SOM http://en.wikipedia.org/wiki/Self-organizing_map to calculate best matching codebook entry from input vector using Euclidian distance method.

I have documented these experimental features in my blog as well as test results:

http://ag1le.blogspot.com/2012/05/fldigi-adding-matched-filter-feature-to.html

I am looking for software developers who can compile this from FLDIGI tar ball, and don't need my support to get this running in their setup.

The software is alpha quality and not ready for broader distribution. If you have interest in testing/improving this software let me know. 
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