Israel Lectures ,

Sept. 27 to Oct.6, 2005


Hebrew University of Jerusalem (HUJI), Givat Ram Campus;

Weizmann Institute of Science, Rehovot;

Bar-Ilan University Tel Aviv, Ramat Gan Campus.





Introduction to Interference Networks

Gerd Heinz, GFaI Berlin,




Applying physical parameters, like velocity, spike-like time functions and spherical arrangements to neural (weight- or pattern-) networks, they change their properties in a fundamental way. We will call them Interference Networks (IN).

Input locations appear mirrored on the output field - a known phenomenon from bio-medical researches.  Adjacent neurons cannot excite one another, nets have to be cleaned before they work, slowness increases memorized capacity and location sensitivity and learning occurs on defined points only. Even elementary functions of neurons change. In this new world everything changes. The behavior of such nets covers properties of known nerve experiments, like Singers synchronization, Penfields "Homunculus", the zoom lens of visual attention, pain, auditory maps or somato-topic maps.

New questions appear:

By physical means IN appear as genus over code- and frequency- selective and projective networks. Possible applications range from optical lens systems, acoustic imaging, digital filters, frequency maps, antenna pattern up to classic neural nets (as a special class of time-restricted networks).

Investigations of IN can help to define possible directions of experimental research.

As an illustration how somatotopic cards work, years before I created the Acoustic Camera technology, which got different awards within Germany, see

Here the image pixels work comparable to interfering neurons.





0 Introduction

            Looking behind Jeffress model of sound localization

            Example for mirror property

            Thumb experiment

            Andrews squid experiments

            Acoustic Camera example


1 Impulse-Waves on Wires

            Consequences of the integrate-and-fire-principle

            Waves on short- circuited nets of wires

            The wave- field-of-function concept

            Multiplication und addition of time functions

            Correlation of monopolar signals

            Equation extraction

            Reflection and refraction


2 Interference Circuits (IC)

            Simplest ICs

            Neuronal basic functions

            Projective ICs

            Superposition: normal and "eating" waves

            Inhibition by excitement



3 Cross- and Self-Interference Properties


            Code maps

            Frequency maps

            Filter-theoretical analogue


4 Projective Properties

            Zooming und movement (scaling)

            Conjunction and permutation

            Permutations in somatotopic and autonomous fields

            N-dimensionality (over-conditioning)

            Reconstructing pseudo- wave fields


5 Projection Circuits

            Colored interference systems


            Declined maps

            h-, e-, p-, k- inversions


6 Calculating simple ICs

            Mask algorithm

            Reconstruction contra projection

            Channel number and cross- interference distance

            Cross- interference overflow (pain?)

            Properties for somato-topic resolution

            Inter-medial projections (dolphin, bat)


7 Discussion of IC-Examples

            Noise maps



            Memorized volume


            Visual Cortex

            Equilibrium circuits, rule of glia

            Singers synchronization


8 Demonstration

            Acoustic image

            Acoustic movie

            Frequency images and movies

            Source separation






Dr. G. Heinz, GFaI (Society for the Promotion of Applied Informatics)

Rudower Chaussee 30, 12489 Berlin

Tel.: +49 30 6392-1652/ -1600, Fax: -1602



"After 3 books, 80 patents and 130 publications I do no longer believe in the contents of the written word."  Michael Goessel, 1990