文件名称:rpe
下载
别用迅雷、360浏览器下载。
如迅雷强制弹出，可右键点击选“另存为”。
失败请重下，重下不扣分。
如迅雷强制弹出，可右键点击选“另存为”。
失败请重下，重下不扣分。
介绍说明－－下载内容均来自于网络，请自行研究使用
Train a two layer neural network with a recursive prediction error
％ algorithm ("recursive Gauss-Newton"). Also pruned (i.e., not fully
％ connected) networks can be trained.
％
％ The activation functions can either be linear or tanh. The network
％ architecture is defined by the matrix NetDef , which has of two
％ rows. The first row specifies the hidden layer while the second
％ specifies the output layer.-Train a two layer neural network with a recursive prediction error algorithm ( recursive Gauss-Newton ). Also pruned (ie, not fully connected) networks can be trained. The activation functions can either be linear or tanh. The network architecture is defined by the matrix NetDef, which has of two rows. The first row specifies the hidden layer while the second specifies the output layer.
％ algorithm ("recursive Gauss-Newton"). Also pruned (i.e., not fully
％ connected) networks can be trained.
％
％ The activation functions can either be linear or tanh. The network
％ architecture is defined by the matrix NetDef , which has of two
％ rows. The first row specifies the hidden layer while the second
％ specifies the output layer.-Train a two layer neural network with a recursive prediction error algorithm ( recursive Gauss-Newton ). Also pruned (ie, not fully connected) networks can be trained. The activation functions can either be linear or tanh. The network architecture is defined by the matrix NetDef, which has of two rows. The first row specifies the hidden layer while the second specifies the output layer.
(系统自动生成,下载前可以参看下载内容)
下载文件列表
rpe.m