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agf.readme
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1999-03-02
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Short: AGF - n*8-bit Sample Pre-Packing Processor
Author: olethros@geocities.com (Christos Dimitrakakis)
Uploader: olethros@geocities.com (Christos Dimitrakakis)
Type: util/pack
OVERVIEW
AGF is a sample pre-processor. It transofrms the data into a form having very
little information content. This makes it easier for compression programs to
pack it down to a small size. AGF combined with GZIP gives an average
compression of 50% and it is always better than any other compression method on
its own.
SUMMARY
AGF - Adaptive Gradient-descent FIR filter.
This is a neural-network-like adaptive FIR filter. The adaptation is
deterministic, which means that the sample can be recovered from the processed
file without needing to save an FIR coefficients to it as well. Adaptation is
done on-line, on a sample-by-sample basis.
USAGE
AGF sample processed_sample
The processed sample can then be efficiently packed with any kind of packer.
I recommend xpk (xGZIP or xSQSH). lha/lzx will also do :)
The results are always MUCH better.
BEWARE! This version is just for illustration puproses and it cannot retrieve
sample data from a processed sample.
TODO
Make it reconstruct samples
Make an xpksublib out of it.
Add options for adjusting the number of coefficients and adaptation rate.
(I have not tested it with 16-bit samples, but the adaptation process might be
able to do it. Give it a try. [the only snag is that the LSB is unsigned, while
I'm reading signed data. It would be guaranteed to work if I added a -128 bias
to all odd bytes.. or if I added coefficients for adaptive bias.])
BUGS
No bugs? Impossible!
Bugs Reports to olethros@geocities.com with "AGF BUG" as the subject message please
SEE ALSO
see also dev/basic/gasp.lha for a similar pre-processor where the adaptive
process is controlled by a Genetic Algorithm
============================= Archive contents =============================
Original Packed Ratio Date Time Name
-------- ------- ----- --------- -------- -------------
20944 11176 46.6% 14-Jan-99 15:32:32 AGF
1840 986 46.4% 14-Jan-99 15:36:16 agf.readme
-------- ------- ----- --------- --------
22784 12162 46.6% 16-Jan-99 19:57:32 2 files