Convergence of batch gradient learning algorithm with smoothing L1/2 regularization for Sigma–Pi–Sigma neural networks

Sigma–Pi–Sigma neural networks are known to provide more powerful mapping capability than traditional feed-forward neural networks. The L1/2 regularizer is very useful and efficient, and can be taken as a representative of all the Lq(0