Technical report available

[Ralph Linsker]

*********  FOR CONNECTIONISTS ONLY - PLEASE DO NOT FORWARD  ***********
****************  TO OTHER BBOARDS/ELECTRONIC MEDIA *******************

The following report (IBM Research Report RC 14195, Nov. 1988)
is available upon request to:

                  lin2 @ ibm.com

It will appear in: Advances in Neural Information Processing Systems 1,
ed. D. S. Touretzky (San Mateo, CA: Morgan Kaufmann), April 1989.

                  "An Application of the Principle of
                    Maximum Information Preservation
                            to Linear Systems,"

                               Ralph Linsker

          This paper addresses the  problem of determining the weights
          for a set  of linear filters (model "cells") so  as to maxi-
          mize the ensemble-averaged information  that the cells' out-
          put values  jointly convey  about their input  values, given
          the statistical properties of the ensemble of input vectors.
          The quantity  that is  maximized is the  Shannon information
          rate, or equivalently the average mutual information between
          input and output.* Several models for the role of processing
          noise are  analyzed, and the biological  motivation for con-
          sidering  them is  described.   For simple  models in  which
          nearby input  signal values  (in space  or time)  are corre-
          lated, the  cells resulting  from this  optimization process
          include  center-surround   cells  and  cells   sensitive  to
          temporal variations in input signal.

  *The possible relation between this optimization principle and the
   organization of a sensory processing system is discussed in:
   R. Linsker, Computer 21(3)105-117 (March 1988).  If you
   would like a reprint of the Computer article, please so note.