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updated 5 months ago

Regression with Gradient Descent by Shujaat Khan

Regression with Gradient Descent; A coefficient finding technique for the desired system model (regression, descent gradient, machine learning)

Arbitary.m

Exp_Pred.m

Linear_Pred.m

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updated 2 years ago

Kohonen Self Organizing Feature Maps (SOFM) for Simulink. by Marcelo Fernandes

A implementation of the Kohonen Self Organizing Feature Maps (SOFM) algorithm for Simulink. (ann, som, sofm)

weights2DView(t,x,u,flag,maxVector,grid,updateFig)

ANN_SOFM

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updated 2 years ago

The matrix implementation of the two-layer Multilayer Perceptron (MLP) neural networks. by Marcelo Fernandes

The matrix implementation of the two-layer Multilayer Perceptron (MLP) neural networks. (ann, mlp, backpropagation)

Y=runMLP(X,Wx,Wy)

[Wx,Wy,MSE]=trainMLP(p,H,m,mu,alpha,X,D,epochMax,MSETarget)

XOR_Example.m

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updated 2 years ago

Multilayer Perceptron Neural Network Model and Backpropagation Algorithm for Simulink by Marcelo Fernandes

Multilayer Perceptron Neural Network Model and Backpropagation Algorithm for Simulink. (ann, mlp, backpropagation)

ANN_MLP_BP_Batch_Mode_Training

ANN_MLP_BP_Incremental_Mode_Training

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updated 2 years ago

The Radial Basis Function (RBF) with LMS algorithm for Simulink by Marcelo Fernandes

The Radial Basis Function (RBF) with LMS algorithm for Simulink. (ann, rbf, artificial neural net...)

ANN_RBF_LMS

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updated 2 years ago

The Radial Basis Function (RBF) using pseudo-inverse method for Simulink by Marcelo Fernandes

The Radial Basis Function (RBF) using pseudo-inverse method for Simulink. (ann, rbf, pseudoinverse)

ANN_RBF_Pseudo_Inverse

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updated 2 years ago

Spike Timing-Dependent Construction Simulation by Toby Lightheart

Simulation of an STDP-based constructive algorithm for spiking neural networks (simulation, modeling, artificial neural net...)

stdc_sim.m

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updated 3 years ago

Rprop by Roberto Calandra

Rprop training for Artificial Neural Networks (artificial neural net..., neural network, nn)

Demo_Rprop_1(batch)

Demo_Rprop_2(batch)

RNN.MSE(inputs,targets)

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