<FONT face=Verdana>By analyzing the impact of the input factors on the output value in nonlinear function

it is suggested that when the input factors are independent

the Fourier Amplitudes which showing sensitivity values are relied mainly on the fundamental frequency. As a result

a fast pruning algorithm for the hidden neurons in the neural network is proposed based on the Fourier amplitude sensitivity test method. In essence

the Fourier amplitudes on the assigned frequencies of the hidden layer outputs are computed. Then the sensitivity of each hidden neuron to the neural network output is obtained. Finally

the redundant hidden neurons are pruned according to their sensitivity values to obtain a network with compact structure. The propose method is used in the soft measurement for Chemical Oxygen Demand(COD)

which is a quality parameter of waste water. The experimental result shows that our proposed method is much faster than the Fourier amplitude sensitivity test method. The remaining neurons are the same after pruning for the two methods .