一、訓練函數
1、traingd
Name：Gradient descent backpropagation （梯度下降反向傳播算法 ）
Description：triangd is a network training function that updates weight and bias values according to gradient descent.
2、traingda
Name：Gradient descent with adaptive learning rate backpropagation(自適應學習率的t梯度下降反向傳播算法)
Description：triangd is a network training function that updates weight and bias values according to gradient descent with adaptive learning rate. it will return a trained net (net) and the trianing record (tr).
3、traingdx (newelm函數默認的訓練函數)
name:Gradient descent with momentum and adaptive learning rate backpropagation(帶動量的梯度下降的自適應學習率的反向傳播算法)
Description：triangdx is a network training function that updates weight and bias values according to gradient descent momentum and an adaptive learning rate.it will return a trained net (net) and the trianing record (tr).
4、trainlm
Name：Levenberg-Marquardt backpropagation （L-M反向傳播算法）
Description：triangd is a network training function that updates weight and bias values according toLevenberg-Marquardt optimization. it will return a trained net (net) and the trianing record (tr).
注：更多的訓練算法請用matlab的help命令查看。
二、學習函數
1、learngd
Name：Gradient descent weight and bias learning function （梯度下降的權值和閾值學習函數）
Description：learngd is the gradient descent weight and bias learning function, it will return the weight change dW and a new learning state.
2、learngdm
Name：Gradient descent with momentum weight and bias learning function （帶動量的梯度下降的權值和閾值學習函數）
Description：learngd is the gradient descent with momentum weight and bias learning function, it will return the weight change dW and a new learning state.
注：更多的學習函數用matlab的help命令查看。
三、訓練函數與學習函數的區別
學習函數的輸出是權值和閾值的增量，訓練函數的輸出是訓練好的網絡和訓練記錄，在訓練過程中訓練函數不斷調用學習函數修正權值和閾值，通過檢測設定的訓練步數或性能函數計算出的誤差小於設定誤差，來結束訓練。
或者這么說：訓練函數是全局調整權值和閾值，考慮的是整體誤差的最小。學習函數是局部調整權值和閾值，考慮的是單個神經元誤差的最小[1]。
參考鏈接：【1】 https://zhidao.baidu.com/question/1883990061249711708.html?fr=iks&word=matlab%D6%D0traingdx%BA%CDlearngdm%B5%C4%C7%F8%B1%F0&ie=gbk