GaryGaulin
Posts: 5385
Joined: Oct. 2012
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| Quote (N.Wells @ May 21 2016,07:43) | This allows them to calculate the chance of false positive signals, which in turn allows them to calculate the efficieny of the system in distinguishing true signals from noise.
| Quote | | In the above example, doubling the number of synapses and hence introducing a 50% noise tolerance, increases the chance of error to only 1.6 × 10^−18. |
I'm skipping over the significant portion of the paper that discusses how all this translates to learning rules for memorization of sequences, but "a network of standard linear or non-linear neurons with a simplified dendrite structure cannot easily implement these activation and learning rules."
This in some ways corresponds to your "confidence evaluation". In particular, you are going to get all excited that the authors talk about incrementing and decrementing............ |
There is no confidence "evaluation" just confidence "levels" associated with each data element stored in memory.
And no, a single neuron learning how to reliably respond to a given set of sensory inputs is indicative of self-organization of a memory-wide addressing circuit made of made of many neurons.
Spare me the long pompous speeches about what authors in another area of science are writing about. I rely on neuroscience related research for clues how the human brain is wired together as I expect it to be, but I am not doing what everyone else is doing and I am proud of that even though you spit on me for not doing what everyone else does.
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The theory of intelligent design holds that certain features of the universe and of living things are best explained by an intelligent cause, not an undirected process such as natural selection.
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