Author: Christophe Theron
Date: 00:22:15 07/03/03
Go up one level in this thread
On July 02, 2003 at 13:13:43, Landon Rabern wrote: >On July 02, 2003 at 02:18:48, Dann Corbit wrote: > >>On July 02, 2003 at 02:03:20, Landon Rabern wrote: >>[snip] >>>I made an attempt to use a NN for determining extensions and reductions. It was >>>evolved using a GA, kinda worked, but I ran out of time. to work on it at the >>>end of school and don't have my computer anymore. The problem is that the NN is >>>SLOW, even using x/(1+|x|) for activation instead of tanh(x). >> >>Precompute a hyperbolic tangent table and store it in an array. Speeds it up a >>lot. > >Well, x/(1+|x|) is as fast or faster than a large table lookup. The slowdown >was from all the looping necessary for the feedforward. > >Landon A stupid question maybe, but I'm very interested by this stuff: Do you really need a lot of accuracy for the "activation function"? Would it be possible to consider a 256 values output for example? Would the lack of accuracy hurt? I'm not sure, but it seems to me that biological neurons do not need a lot of accuracy in their output, and even worse: they are noisy. So I wonder if low accuracy would be enough. Christophe
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