论文部分内容阅读
提出了有监督线性特征映射网络（ＳＬＦＭ），并应用于刀具磨损量实时估计，研究了网络参数对学习速度和网络性能的影响，并与误差反馈式多层前向网络（ＢＰ网络）进行对比。研究表明，ＳＬＦＭ网络具有学习快、精度高的优点，具有广泛的应用前景
A supervised linear feature mapping network (SLFM) is proposed and applied to real-time estimation of tool wear. The influence of network parameters on learning speed and network performance is studied and compared with error feedback multi-layer forward network (BP network) . The research shows that the SLFM network has the advantages of fast learning and high precision, and has a wide range of application prospects