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在复杂的无线环境下建立有效的全天候的数字广播电视实时监控系统对保证信号传输质量是非常必要的,而数字监控接收机的正常工作是监控系统中重要的环节。本文简要介绍了常用的故障模式识别方法和人工神经网络在故障诊断领域的具体应用。论述了径向基网络和概率神经网络的基本原理,通过这两种优秀的模式分类网络跟传统模式识别方法的matlab仿真对比,确定采用能够同时诊断多接收机故障的径向基函数网络。
The establishment of an effective all-weather digital broadcast television real-time monitoring system under complex wireless environment is necessary to ensure signal transmission quality, and the normal operation of the digital monitoring receiver is an important part of the monitoring system. This article briefly introduces the commonly used fault pattern recognition method and artificial neural network in the field of fault diagnosis. The basic principle of radial basis network and probabilistic neural network is discussed. By comparing the two excellent pattern classification networks with the traditional pattern recognition method, the radial basis function network which can simultaneously diagnose multi-receiver faults is determined.