论文标题
Si板半径对神经网络处理的光声信号的影响
Si plate radius influence on the photoacoustic signal processed by neural networks
论文作者
论文摘要
样品半径对通过未经遗嘱和差异信号训练的神经网络处理的总光声信号的影响，以仔细分析了20至20 kHz的调制频率。这是针对针对400毫米厚的Si N型板生成的信号的，其半径从2到7 mm不等。发现经过未订阅或差异信号训练的网络可为2至3 mm之间的样品半径提供最佳预测，该预测接近1.5 mm的使用麦克风孔径。仅使用未经发生信号训练的网络为样品半径提供了与麦克风尺寸相当的样品半径的最佳结果。所获得的结果证明了针对样品半径等于麦克风孔径的理论模型的有效性合理，并表明使用与此孔径相当的半径的实验必要性。
The effect of the sample radius on the total photoacoustic signal processed by neural networks trained with undistorded and distorded signals is carefully analized for modulation frequencies from 20 to 20 kHz. This is done for signals generated for a 400micrometers thick Si n-type plate, whose radius varies from 2 to 7 mm. It is found that the networks trained with both undistorded or distorded signals yield the best predictions for sample radii between 2 and 3 mm, which is close to the used microphone aperture radius of 1.5 mm. The network trained only with undistorted signals gives the best results for sample radii comparable to the microphone dimensions. The obtained results justify the validity of a theoretical model derived for a sample radius equals to the microphone aperture and indicate the experimental necessity to use samples with radii comparable to this aperture.
