Neural Network Self-Organizing Maps Control Feedback Methods Models of Computation
Issue Date:
2009
Publisher:
Institute of Information Theories and Applications FOI ITHEA
Abstract:
This paper shows some ideas about how to incorporate a string learning stage in self-organizing
algorithms. T. Kohonen and P. Somervuo have shown that self-organizing maps (SOM) are not restricted to
numerical data. This paper proposes a symbolic measure that is used to implement a string self-organizing map
based on SOM algorithm. Such measure between two strings is a new string. Computation over strings is
performed using a priority relationship among symbols; in this case, symbolic measure is able to generate new
symbols. A complementary operation is defined in order to apply such measure to DNA strands. Finally, an
algorithm is proposed in order to be able to implement a string self-organizing map.
Description:
* Supported by projects CCG08-UAM TIC-4425-2009 and TEC2007-68065-C03-02