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cs444cass:nnet

ANN with Elixir -- An Artificial Biological Approach

Project Description

Goal: Make a Artificial Neural Network that is as close to its biological sibling as possible. but wat iif i used assembly and elixir

Neural Networks are mirrored after the biological components in our brain, and the original theory for Machine Learning was put forward jointly by Neuro-Scientist and Neuro-Physicist, Dr. Walter Pitt Jr & Warren McClulloch. While today's field has changed from its original idea, the question arises if that is the best way, or if mimicking the original “computer”(and I'm not talking about the 1000 women in a bunker during WWII that computed everything by hand), our brain, might actually be better and more efficient. One similar thing between Neurons and Electrical circuits is both can be reconfigured to perform different functions (Carl).

To reach the goal of mimicking the program to our human brain, the first job was to determine which language might best fit it. The choice was Elixir. Pattern-Matching already matches the Neurochemical and Neurochemical Receptors relationship between Axons and Dendrites in the Synapses. Furthermore, the primitives of Elixir appear to imitate the brain as well: Spawn - the creation of new neurons, Send - Axons, Receive - Dendrites.

ANN Resources

Alt Neural Models

Elixir+Raspberry Pi Resources

Reporting

The progress log is a weekly narrative of the project in a form similar to this http://dokuwiki.sewanee.edu/doku.php?id=pdc:mcgriff2017:progress. Describe what was done, what worked, what didn't, and add links to new work generated. Example from previous internship.

cs444cass/nnet.txt · Last modified: 2019/02/04 21:38 by ursiidae