Copy CodeCopy Command This example shows how to generate plain CUDA® MEX from MATLAB® code and denoise grayscale images by using the denoising convolutional neural network (DnCNN [1]). The pretrained denoising network estimates the noise in a noisy image and then removes it, resulting ...
Matlab Code 如下1 2 3 4 5 6 7 for i = 1 : n thetaPlus = theta; thetaPlus(i) = thetaPlus(i) + EPS; thetaMinus = theta; thetaMinus(i) = thetaMinus(i) - EPS; gradApprox(i) = (J(thetaPlus) - J(thetaMinus)) / (2 * EPS); end最后检查 gradApprox 是否约等于之前计算的...
net = network net.numInputs = 1 net.numLayers = 2 Alternatively, you can create the same network with one line of code. net = network(1,2) Create Feedforward Network and View Properties This example shows how to create a one-input, two-layer, feedforward network. Only the first ...
Mdlis a trainedClassificationNeuralNetworkclassifier. You can use dot notation to access the properties ofMdl. For example, you can specifyMdl.TrainingHistoryto get more information about the training history of the neural network model. Evaluate the performance of the classifier on the test set by...
Select the beam pair with the highest average RSRP as the final predicted beam pair by the neural network. The example measures the effectiveness of the proposed method using two metrics: average RSRP and top-K accuracy. This figure shows the main processing steps....
If you notice discrepancies between the network in MATLAB and in Simulink, please check that the initial values are set properly in the Simulnk block using 'getsiminit'. Refer to the attached script for a simple example on how to do so. ...
Neural Network ArchitectureDatastore OutputExample Output Single input layer Table or cell array with two columns. The first and second columns specify the predictors and targets, respectively. Table elements must be scalars, row vectors, or 1-by-1 cell arrays containing a numeric array. ...
This MATLAB function returns a function fitting neural network with a hidden layer size of hiddenSizes.
This MATLAB function returns a function fitting neural network with a hidden layer size of hiddenSizes.
example [net,classNames] = imagePretrainedNetwork(name)returns the specified pretrained neural network and its class names. [net,classNames] = imagePretrainedNetwork(___,Name=Value)specifies options using one or more name-value arguments, in addition to any combination of input arguments from previ...