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中文摘要：
讨论了一种神经网络算子f_n(x)=sum from -n~2 to n~2 (f(k/n))/(n~α)b(n~(1-α)(x-k/n)),对f(x)的逼近误差|f_n(x)-f(x)|的上界在f(x)为连续和N阶连续可导两种情形下分别给出了该网络算子逼近的Jackson型估计.
英文摘要：
A kind of neural network operator f_n(x)=sum from -n~2 to n~2 (f(k/n))/(n~α)b(n~(1-α)(x-k/n)), is considered and the upper bounds of approximation errors |f_n(x)-f(x)| are discussed.The Jackson- type estimates are obtained respectively when f(x) being continuous and continuously differentiable for N-times.
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