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Originally Posted by neuron2
If you don't actually *have* a network of parallel units, but instead simulate it serially, as you would on a PC, you are doing a pointless thing, unless you are just trying to *develop* parallel neural algorithms.
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I am not too sure about this. ANN processing is done extensively in share market predictions using serial input. For instance in the 3x3 grid used in edge detection is input as 9 nodes in ANN and works same except the weights are determined in a different fashion and some times more aptly.
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I haven't seen such processing of video on PCs, presumably because it is dreadfully slow.........
Even if that were achieved, running it on a serial processor would probably be way too slow.
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The edge detection training took a couple of minutes but actual processing was as fast as the usual edge detection algorithms.
As for Zarxarax,s suggestion of noise elimination, I have been thinking using my Fan Filter as a training material. Right now I am not sure as to how many output nodes I need. I am also to understand in more detail the requirements of number of nodes, their starting weights, the number of layers etc.
I am aware that all my efforts may not yield any practical or usable process and has to be discarded. However at this stage I am not put off by those considerations. On the otherhand I am optimistic about the outcome.
A google search for ANN applications indicates mostly stock market predictions, and some medical image Analysis. I am sure some part of this analysis will be applicable to video images also. May be similar to stock prediction, motion can be predicted?