Single Neuron Character Recognition Essay

1367 Words Sep 22nd, 2013 6 Pages
Nelson Mandela Metropolitan University

Character
Recognition – Single
Neuron
WRCI 411 – Assignment 1

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August 2013

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WRCI 411 – Assignment 1

August 2013

Contents
List of Figures and Tables ........................................................................................................................ 1
Figures ................................................................................................................................................. 1
Tables .................................................................................................................................................. 1
Theory
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The overall error should decrease and when it is below 0.005 the teaching code ends and testing starts.
The brief recommends 20 characters in the teaching set, but as can be seen further in this report, very accurate results were found with just 8 – so 9 teaching characters were used.

Testing
Testing is done by finding the neuron outputs of a large random set of values (numbers, letters and random static – including non-binary inputs, negatives and decimal estimations of the taught letter).
The code finds the dot product between each input vector and the weight matrix and outputs a value from 0-1. The code then makes this binary or undefined as explained below.

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WRCI 411 – Assignment 1

August 2013

Experiment
The experiment aims to find the effects of different values for learning rate, accuracy, where the taught letter is positioned in the teaching set and the number of vectors in the teaching set and what effect the letter being taught has. The experiment should also prove the robustness, accuracy and reliability of the neuron. The experiment performed for this report makes use of an iteration counter built into the section of code that manipulates the weight vector to represent the time taken to perform the learning.
The code outputs 4 parameters, 3 vectors and a number. A vector

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