Classifying 2D patterns (images of alphabet letters) using Perceptron rule

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hi i have asked this question couple of times in different forms but didnt get any real answers
i have 520 images of alphabet letters (20x26) and need to use single layer perceptron to classify them using LOOCV (leave one out cross validation)
my images are grayscale but i need to turn them into bipolar values (-1 and 1) this part isnt a problem
i know i need to use newp to creat the net and train it
but i have no idea how or where to even start
id like to at least know an algoritem or guide line of where to start and where to get
im not a computer student im EE and no idea how or even what i need to do
thank you

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