M. Jändel
Pattern Recognition as an Internalized Motor Programme
1400 - 1408
2010
4
9
International Journal of Computer and Information Engineering
https://publications.waset.org/pdf/4785
https://publications.waset.org/vol/45
World Academy of Science, Engineering and Technology
A new conceptual architecture for lowlevel neural
pattern recognition is presented. The key ideas are that the brain
implements support vector machines and that support vectors are
represented as memory patterns in competitive queuing memories. A
binary classifier is built from two competitive queuing memories
holding positive and negative valence training examples respectively.
The support vector machine classification function is calculated in
synchronized evaluation cycles. The kernel is computed by bisymmetric
feedforward networks feed by sensory input and by
competitive queuing memories traversing the complete sequence of
support vectors. Temporary summation generates the output
classification. It is speculated that perception apparatus in the brain
reuses structures that have evolved for enabling fluent execution of
prepared action sequences so that pattern recognition is built on
internalized motor programmes.
Open Science Index 45, 2010