77 research outputs found
Artificial Neuron Modelling Based on Wave Shape
This paper describes a new model for an artificial neural network processing
unit or neuron. It is slightly different to a traditional feedforward network
by the fact that it favours a mechanism of trying to match the wave-like
'shape' of the input with the shape of the output against specific value error
corrections. The expectation is then that a best fit shape can be transposed
into the desired output values more easily. This allows for notions of
reinforcement through resonance and also the construction of synapses.Comment: Publishe
New Ideas for Brain Modelling
This paper describes some biologically-inspired processes that could be used
to build the sort of networks that we associate with the human brain. New to
this paper, a 'refined' neuron will be proposed. This is a group of neurons
that by joining together can produce a more analogue system, but with the same
level of control and reliability that a binary neuron would have. With this new
structure, it will be possible to think of an essentially binary system in
terms of a more variable set of values. The paper also shows how recent
research associated with the new model, can be combined with established
theories, to produce a more complete picture. The propositions are largely in
line with conventional thinking, but possibly with one or two more radical
suggestions. An earlier cognitive model can be filled in with more specific
details, based on the new research results, where the components appear to fit
together almost seamlessly. The intention of the research has been to describe
plausible 'mechanical' processes that can produce the appropriate brain
structures and mechanisms, but that could be used without the magical
'intelligence' part that is still not fully understood. There are also some
important updates from an earlier version of this paper
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