From: forrest@nobozo.CS.Berkeley.EDU (Jon Forrest)
Newsgroups: comp.compression
Subject: Is This Possible (or is it B.S)? [200:1 Lossless Compression]
Date: 22 Jan 1993 00:08:26 GMT
Organization: University of California, Berkeley
Distribution: world
NNTP-Posting-Host: nobozo.cs.berkeley.edu

I'm the first to admit that I don't know anything about compression.
That's why I'm extremely puzzled by the following abstract of a talk that's
going to be given here at Berkeley. Is this B.S. or should I raise
my arms and cry hallelujah?

---
                          CS 298-9
                    Sequoia 2000 Seminar

            Joe Bugajski, Founder and President
                        Triada Ltd.

                 TRIADA'S 200:1 (LOSSLESS)
                  DATA COMPRESSION ENGINE

                  Friday, January 29, 1993
                   1:00 p.m. - 3:00 p.m.
                      608-7 Evans Hall


     Triada, a development stage company located  in  Michi-
gan,  has  developed  an encoding transform capable of up to
200:1 lossless data compression.  The theoretical  underpin-
ning of the transform is believed to extend classical infor-
mation theory.  The new theory treats an information  source
that  evolves  from  a  null state to stationarity.  A model
based on the theory consists of an  energetically  conserva-
tive  field of uniformly distributed photons and an observer
randomly walking through this field.  Observations are  made
with  a bandwidth-limited set of transducers (an "eye") that
respond to events during the walk.  Each transducer  in  the
set  is  uniquely tuned to a sub-band and generates a signal
when it receives a signal.   The  output  signals  from  the
input  set  of transducers are "observed" by a second set of
transducers (a mid brain), except the bandwidth limit of the
second  set  of  transducers is a non-overlapping lower fre-
quency range than the bandwidth of the first set  of  trans-
ducers,  and  only  events from the first transducer set are
"seen" by the second.  This procedure is repeated n times or
through N levels or "time domains," td.  These levels form a
hierarchy of planes of "memories," (a  visual  cortex),  and
individual (associative) memories (transducers) are unique.

     The dynamics of the digital computer equivalent of this
model  were studied during the past four years.  In particu-
lar, the size of the memory sets was measured as a  function
of events "seen" at level td, where the input data were (not
compressed)  randomly  collected,  large  samples  of  text,
black/white  images, eight-bit grey scale images, and copies
of data bases.  The number of memories  formed  were  always
Boltzman  distributed,  and  sub-band  frequencies  at every
memory level, or td, exhibited by the Self- Organized Criti-
cality  (SOC)  theory  [Bak et al. (1987) Phys Rev Lett: 59,
381-384).  Because the memories self organize and the  digi-
tal  version  of  the  transform  is invertible, a real-time
digital implementation of the memory structure can be built.
Additional tests are underway to confirm these results for a
larger variety of data types using greater than 10  gigabyte
data samples.

     Triada's founder and chief theoretician, Joe  Bugajski,
a  mathematician,  spent  the  first  13 years of his career
doing information system  design  at  Ford  Motor  Company's
Research  and  Engineering  Center.  He has devoted the last
seven years to data compression and related topics.
-- 
Anything you read here is my opinion and in no way represents the Univ. of Cal.
Jon Forrest WB6EDM	 forrest@postgres.berkeley.edu	 510-643-6764
Newsgroups: comp.compression