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于 2020-04-01 发布
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代码说明:

说明:  极限学习机是由黄广斌在2005年作为一种新的单隐层前馈神经网络提出的,具有与神经网络(NN)相同的全局逼近性质,且其参数学习无需迭代,速度明显快于现有的神经网络。目前在岩性识别、LF终点温度软测量、穿孔机导盘转速测量、软测量建模、图像识别等方面有所应用,但将其用于图像分割中的应用还较少。(Limit learning machine was proposed by Huang guangbin as a new single hidden layer feedforward neural network in 2005. It has the same global approximation property as neural network (NN), and its parameter learning does not need iteration, and its speed is significantly faster than the existing neural network. At present, it has some applications in lithology identification, lf terminal temperature soft measurement, perforator guide plate speed measurement, soft measurement modeling, image recognition and so on, but its application in image segmentation is less.)

文件列表:

elm\ELM.m, 9151 , 2011-03-26
elm\elm_predict.m, 3763 , 2004-05-10
elm\elm_train.m, 5645 , 2004-05-10
elm\sinc-1.m, 709 , 2004-04-16
elm\sinc-2.asv, 760 , 2011-05-06
elm\sinc.m, 709 , 2011-05-14
elm\sinc_mean.m, 768 , 2004-04-17
elm\sinc_test1, 114277 , 2004-04-17
elm\sinc_train1, 114566 , 2004-04-17
elm, 0 , 2011-07-13
elm\ds_elm_predict2.asv, 3993 , 2011-06-06
elm\ds_elm_predict2.m, 4079 , 2011-06-06
elm\dt2.asv, 427 , 2011-07-14
elm\dt2.m, 434 , 2011-07-14
elm\ELM2-dt.asv, 9325 , 2011-07-13
elm\ELM2.asv, 9333 , 2011-07-25
elm\ELM2.m, 9359 , 2011-08-18
elm\ELM2_dt.m, 9323 , 2011-07-14
elm\elm_predict2.asv, 3803 , 2011-05-15
elm\elm_predict2.m, 3802 , 2011-06-06
elm\elm_train2.m, 5660 , 2011-05-15
elm\sinc_mean2.asv, 1278 , 2011-05-14
elm\sinc_mean2.m, 1172 , 2011-05-14
elm\sinc_test, 114426 , 2011-05-14
elm\sinc_train, 114464 , 2011-05-14

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