文件名称:Backpropagation--5
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Backpropagation, an abbreviation for backward propagation of errors , is a common method of training artificial neural networks used in conjunction with an optimization method such as gradient descent. The method calculates the gradient of a loss function with respects to all the weights in the network.-Backpropagation, an abbreviation for backward propagation of errors , is a common method of training artificial neural networks used in conjunction with an optimization method such as gradient descent. The method calculates the gradient of a loss function with respects to all the weights in the network.
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下载文件列表
| 文件名 | 大小 | 更新时间 |
|---|---|---|
|
| ||
| Backpropagation 5\Automated Regularization (trainbr).m | ||
| ..................\Batch Gradient Descent (traingd).m | ||
| ..................\Batch Gradient Descent with Momentum (traingdm.m | ||
| ..................\feedfor.m | ||
| ..................\Fletcher-Reeves Update (traincgf).m | ||
| ..................\Levenberg-Marquardt (trainlm).m | ||
| ..................\Modified Performance Function.m | ||
| ..................\One Step Secant Algorithm (trainoss).m | ||
| ..................\Polak-Ribiére Update (traincgp).m | ||
| ..................\Powell-Beale Restarts (traincgb).m | ||
| ..................\Quasi-Newton Algorithms (trainbgf).m | ||
| ..................\Resilient Backpropagation (trainrp).m | ||
| ..................\Sample Training Session.m | ||
| ..................\Scaled Conjugate Gradient (trainscg).m | ||
| ..................\Variable Learning Rate (traingda | traingdx).m | |
| Backpropagation 5 |