So here's another project i'm working on cocurrently. A music analyser using neural nets. I'm using the Maate MPEG library to decode mp3s and running them through the neural net to look for classifications. Okay, that made no sense. Here we go. Let's call the program MA. You pass in 2 lists to MA, a list of songs you want to hear and a list of songs that you don't want to hear. You then train the network (a standard FFN) with the lists that you passed in, expecting a result of 1 for a good song and 0 for a bad. I'm currently using the RMS value of each subband as the inputs to the network. Layers: variable node input layer, 20 and 10 node hidden layers, and a 1 node output layer. I want to extend the program so I have multiple nets (RMS, Centroid, Energy Movement, etc) and allow the songs that have a majority of the nets firing to enter the "good" list. I've only programmed in the RMS network so far, and that seems to be working well. I'm looking at a 98% success rate so far... i'll get back to the robot soon...