NeuralNet
Computation functions
ann_calcjac
—
Calculate Jacobian Matrix
ann_compet_activ
—
Competitive Activation Function
ann_compet_init
—
ANN Competitive Network initialization function
ann_d_hardlim_activ
—
Derivative of Hardlimit activation function
ann_d_logsig_activ
—
Derivative of Logistic activation function
ann_d_purelin_activ
—
Derivative of Linear activation function
ann_d_relu_activ
—
Derivative of Rectified linear activation function
ann_d_softmax_activ
—
Derivative of softmax activation function
ann_d_tansig_activ
—
Derivative of Tangent Sigmoid activation function
ann_dist
—
Distance weight function
ann_ffbp_init
—
ANN FeedForward Backpropagation Weight initialization function.
ann_gencluster
—
Generate Cluster of Data
ann_hardlim_activ
—
Hardlimit activation function
ann_logsig_activ
—
Logistic Sigmoid activation function
ann_negdist
—
Negative distance weight function
ann_purelin_activ
—
Linear activation function
ann_relu_activ
—
Rectified linear activation function
ann_softmax_activ
—
Softmax activation function
ann_som_boxdist
—
Box distance function.
ann_som_eudist
—
Euclidean distance function.
ann_som_gridtop
—
Grid topology function.
ann_som_hextop
—
Hexagonal topology function.
ann_som_linkdist
—
Link distance function.
ann_som_mandist
—
Manhattan distance function.
ann_som_randtop
—
Random topology function.
ann_tansig_activ
—
Tangent Sigmoid activation function
ann_training_process
—
Training Process GUI
Neural_Network_Functions
ann_ADALINE
—
ANN ADALINE training function (batch training)
ann_ADALINE_online
—
ANN ADALINE training function (incremental training)
ann_ADALINE_predict
—
ANN ADALINE training function (incremental training with tapped delay)
ann_ADALINE_run
—
ANN ADALINE simulate function.
ann_COMPET
—
ANN Competitive Network.
ann_COMPET_run
—
ANN Competitive Network simulation function
ann_COMPET_visualize2d
—
ANN Competitive Network with 2d animation
ann_COMPET_visualize3d
—
ANN Competitive Network with 3d animation
ann_FFBP_gd
—
ANN FeedForward Backpropagation Gradient Decent training function.
ann_FFBP_gda
—
ANN FeedForward Backpropagation Gradient Decent with Adaptive Learning Rate training function.
ann_FFBP_gdm
—
ANN FeedForward Backpropagation Gradient Decent with Momentum training function.
ann_FFBP_gdx
—
ANN FeedForward Backpropagation Gradient Decent with Adaptive Learning Rate and Momentum training function.
ann_FFBP_lm
—
ANN FeedForward Backpropagation Levenberg–Marquardt algorithm training function
ann_FFBP_run
—
ANN FeedForward Backpropagation Network simulation function
ann_FFBP_sim
—
ann_LVQ1
—
ANN LVQ Network Structure 1.
ann_LVQ_run
—
ANN LVQ Network Simulation function
ann_PERCEPTRON
—
ANN Perceptron training function.
ann_PERCEPTRON_run
—
ANN Perceptron simulate function.
ann_PERCEPTRON_visualize
—
ANN Perceptron training function with visualization.
ann_SOM
—
ANN Self-Orginizing Map (Batch Training)
ann_SOM_online
—
ANN Self-Orginizing Map (incremental training)
ann_SOM_run
—
ANN Self-Orginizing Map Network Simulation function
ann_SOM_visualize2d
—
ANN Self-Orginizing Map with 2d visualization
ann_SOM_visualize3d
—
ANN Self-Orginizing Map with 3d visualization
ann_getToolboxPath
—
Returns the path to the current module.
initialize_parameters
—
Initialize Network Object for Feed-forward Back-Propagation Network (New)
knn
—
K Nearest neighbours classification
model_forward
—
Forward propagation for Feed-forward Back-Propagation Network (New)
nn_eval_performance
—
Evaluate the network performance
nn_onehot
—
One-hot Encoding
nn_split_data
—
Split the data into training and testing dataset
nn_train
—
Feed-forward Back-Propagation Network (New)
Utilities_Functions
ann_imgcrop
—
Image pre-processing function to remove white spaces on all sides of images
ann_imgfeatures
—
Image pre-processing function to extract features from binary image
ann_imgpreprocess
—
Image pre-processing function
Visualization functions
ann_som_plot2d
—
Visualize 2-D Self-Organizing Map
ann_som_plot3d
—
Visualize 3-D Self-Organizing Map
plot3dot
—
3-D Parametric plot for opoints
plot_2group
—
Visulized 2 groups of data, with the data being tagges as 0 and 1 respectively
plot_boundary
—
Plot the data set
plot_weight
—
Plot the boundary for simple perceptron
plotchar
—
Plot a 35 element vector (7 x 5)
plotchar53
—
Plot a 15 element vector as a 5x3 grid.
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