[SOLVED] INT301 Lab 10-Radial Basis Function Neural Networks

Radial Basis Function Neural Networks

The following exercise can be used to model an RBF network

    %Radial Basis Function Network
    clear;close all;

    %Generate training data (input and target)
    p = [0:0.25:4];
    t = sin(p*pi);

    %Define and train RBF Network
    net = newrb(p,t);
    plot(p,t,'*r');hold;

    %Generate test data
    p1 = [0:0.1:4];

    %Test network
    y = sim(net,p1);

    plot(p1,y,'ob');
    legend('Training','Test');
    xlabel('input, p');
    ylabel('target, t');

Part 1

Revise demo.m in Week 6 lab with RBF network, to demonstrate the capability of RBF network to model the XOR logic gate.

Part 2

Demonstrate the capability of an RBF to approximate the function f(t) = sin(t)*exp(-t/20); 0 < t < 50

Implement K-means clustering algorithm for determining the centers. (Hint: you need to write the Matlab code for this part using formulae of RBF network from lecture notes, instead of directly using newrb and sim functions.)