title: Training feedforward neural network for OCR
body: <p>Currently I'm learning about neural networks and I'm trying to create an application that can be trained to recognize handwritten characters. 
  For this problem I use a feed-forward neural network and it seems to work when I train it to recognize 1, 2 or 3 different characters. But when I try to make the network learn more than 3 characters it will stagnate at a error percentage around the 40 - 60%. </p>
  
  <p>I tried with multiple layers and less/more neurons but I can't seem to get it right, now I'm wondering if a feedforward neural network is capable of recognizing that much information. </p>
  
  <p>Some statistics:</p>
  
  <p><strong>Network type:</strong> Feed-forward neural network</p>
  
  <p><strong>Input neurons:</strong> 100 (a 10 * 10) grid is used to draw the characters</p>
  
  <p><strong>Output neurons:</strong> The amount of characters to regocnize</p>
  
  <p><em>Does anyone know what's the possible flaw in my architecture is? Are there too much input neurons? Is the feedforward neural network not capable of character regocnition?</em></p>