Alife and Machine Learning on the X16
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- Posts: 503
- Joined: Sat Jul 11, 2020 3:30 pm
Re: Alife and Machine Learning on the X16
Well, the logistic function is another way of normalizing, but you then have to go full floating point. I've been trying to keep everything in the range [-1..1] to represent all numbers in eight bits.
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- Posts: 503
- Joined: Sat Jul 11, 2020 3:30 pm
Re: Alife and Machine Learning on the X16
The big advantage of limiting neurons to only two inputs is that it turns neural computation from order of (N^2)logN operations into order of N operations for N neurons.
The second advantage is that it makes every neuron into something that can be displayed graphically as 3D: each input is one axis, the output is the third axis. So, the programmer has a much easier time visualizng what each neuron does.
The second advantage is that it makes every neuron into something that can be displayed graphically as 3D: each input is one axis, the output is the third axis. So, the programmer has a much easier time visualizng what each neuron does.