Study of Enhancing Features of Digital Oscilloscope Based on Elman Networks

In this paper, a method for enhancing the measure performance of digital oscilloscope for Amplitude Modulation (AM) signals is presented by applying Elman sptio-temporal neural network. In this method, the demodulation of AM signals is implemented by adopting both "traingdx" and "learnbcf" functions in Elman network; the structure of Elman network is improved by introducing weights and delays from the output layer to the hidden layer; and an additive momentum factor is adopted in gradient learning algorithm. Simulation results demonstrate that the proposed method has faster learning speed, less computational error, and higher measuring robustness and precision.