Neurocomputing: Fundamentals of Computational Neuroscience (Fall 2005)

Assignment 2

1. Implement a perceptron and train it to recognise the digital letters given in pattern1.

2. Plot a training curve, which is the error as a function of training steps.

3. Investigate how much noise in the pattern the perceptron can tolerate before beeing unable to recognize a letter. There are different ways to implement noise, but you could just choose to flip a certain number of bits (but don't flip one twice).

3. Which letter is in pattern2?

Help: The MATLAB function patternDisp.m reads the patterns from the file pattern1 (patternDisp(n), with n=1-26) and pattern2 (patternDisp(0)) and displays them. Look at the code. It uses the Matlab function reshape that can help you to convert the patterns into input vectors.