A local extended Kalman filter training and pruning approach is proposed to
train feedforvard networks with the goal of reducing the computational com
plexity and storage requirement in large-scale practical problems. The perf
ormance of the proposed algorithm is demonstrated for the problem of handwr
itten digit recognition.