A fast and efficient two-phase sequential learning algorithm for spatial architecture neural network

(1) Span-output-weights ωL0, ωL1, …, ωL(L−2) are estimated based on the random generated weights and bias. (2) Feedforward-output-weights ωL(L−1) were trained iteratively through iterative learning.