[Solved] INT301 Lab 12-Competitive Learning

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Competitive Learning

To demonstrate the competitive networks ability to cluster data, a 2-dimensional dataset consisting of 6 Gaussian distributions with small widths will be used. Use the function loadclust1 to get the data and Matlabs plot function to visualize it, e.g.

               >> [P,T] = loadclust1(200);               >> plot(P(1,:),P(2,:),'b*');

Use m-file syn_comp.m in the next 3 exercises.

Exercise 1: Use 100-200 data from the data set, with 6 output neurons and default values for the learning parameters. Does it work?(Note: after setting the parameters, remember to Hit a key to continue in the command window; it is also recommended to keep Figure 1 on top to observe the position changes of output neurons.)

Exercise 2: Use 100-200 data from the data set and 6 output neurons, but try different settings of the learning parameters and conscience learning parameter. Especially, turn off the conscience learning parameter (type n for Use default learning parameters and type 0 for Conscience learning rate) to see if dead neurons appear. (Note: use help learncon in command window if you want to know more about conscience learning parameter.)