2 research outputs found
A new model for classifying DNA code inspired by neural networks and FSA
This paper introduces a new model of classifiers CL(V,E,l,r)
designed for classifying DNA sequences and combining the flexibility of
neural networks and the generality of finite state automata. Our careful
and thorough verification demonstrates that the classifiers CL(V,E,l,r)
are general enough and will be capable of solving all classification tasks
for any given DNA dataset. We develop a minimisation algorithm for
these classifiers and include several open questions which could benefit
from contributions of various researchers throughout the world