In this paper we present the systematic trajectory search

algorithm (STSA) which first globally explores the solution

space then makes thorough local searches in promising areas.

The STSA has been tested on training feedforward neural

networks to solve the n-bit parity problem of various sizes

and two real medical diagnosis problems. The experimental

results show that the feedforward neural networks trained by

the proposed algorithm have very good classification ability.