Reconfigurable neural networks

[GOLDFARB]

    " I am interested in constructive  algorithms  for  neural  networks
      (capable of generating new units and layers in the NN)."
 
 I believe that the current framework of neural networks is not well suited to
 the above task, i.e. for reconfigurable NN. See my message of 27 September.
 Introduction to a fundamentally new model that is "reconfigurable" can be found
 in my Pattern Recognition paper mentioned in the above message and in several
 more resent papers.  Although the example considered in the above paper uses
 nonnumeric operations (and representation) and does not require the learning
 machine to reconfigure itself, the issue of reconfigurability was one of the
 main driving motivations for the proposed model and is partly addressed in the
 more resent papers. Since the proposed model is also valid (and even becomes
 simpler) for vector patterns, an excellent topic (particularly for a thesis)
 would be an application of the model to vector patterns. I would be glad to
 help with the necessary missing details.
 
                                            Lev Goldfarb