NN RIG Lecture

[Chris Christodoulou]

IEEE Neural Networks Regional Interest Group
Chairman: Trevor Clarkson (tgc at kcl.ac.uk)


                       NN RIG LECTURE

      "Applications of Neural Nets and Fuzzy Logic in 
                 Communications Systems"

              by Dr Stamatios Kartalopoulos
            (VP IEEE Neural Networks Council)

   to be held at King's College London, Strand, London WC2
               on Wednesday 29th March 1995
                       at 6.00pm 
               Room 1B23 (Strand Building)

             All are welcome at this lecture

SUMMARY
Neural Networks and Fuzzy Logic have already found wide range applicability.  
The projection is that this trend will keep continuing.  Although the notion 
of neural networks was to escape from the conventional computer, nevertheless, 
to date, many neural network applications still depend on the conventional 
computer; during learning or during normal operation.  The all-neural network, 
independent from the conventional digital computer (during learning and 
operation), and outperforming a conventional computer in equivalent 
functionality with cost/performance as a metric, is yet to come.  
Currently, we see niche applications that address improvements in a specific 
area within a complex system.  Most of the applications described fall in 
this category.
Paradigms used today are math intensive; the neural network problem has been 
shifted from the unknown mental process to an optimization algorithmic problem 
using conventional math.  I cannot believe that the human brain operates on 
equations to estimate and solve a problem, to recognize objects, or to make 
inferences.  I cannot believe that the human brain solves the backpropagation 
algorithm, or any other algorithm when it is trained.  What is needed are 
fresh ideas.  Ideas that go beyond the current conventional paradigms.  Ideas 
that emulate human thinking and map it on a network.  Conventional math is 
good for modelling to use computer tools for emulation and simulation, 
for the time being.  However, conventional math is a mental attractor that 
keeps pulling us back to conventional techniques.  In short, there are many 
Challenges that make the future seem more exciting than ever.