an artificial neuron
is a computational model inspired by the complex natural neural system.
Elements of the artificial neuron
are represented by: m that indicates the number of the neuron input signals; [x.
Digital Hardware Implementation of Artificial Neuron
Model Using FPGA.
As described by Pasquotto (2010) each artificial neuron
functions as a unit with autonomy whose objective is to convert an input signal into another output signal.
The scientists and researchers have successfully completed the development of first artificial neuron
that is amazingly capable of imitating the working of neuron cell with potential to interpret the chemical signals into electrical signals and report to other cells.
An artificial neuron
is the fundamental processing unit of the ANN (15).
is extremely simple abstraction of biological neuron, implemented as element in a program or perhaps as circuits made of silicon (Guo et al.
The basic building blocks that are necessary for FPGA implementation of artificial neuron
are adder, multiplier and nonlinear function that is hardware unfavourable.
The artificial neuron
is a simple mapping model; artificial neuron
model can be expressed as
The body of the artificial neuron
consisted of a sum function (linear combiner [SIGMA]), represented by the weighted sum of the values received by the neuron through the synapses and summed to the bias value that is externally applied and has the effect of increasing or decreasing the output value ([v.
The basic element in the NN is a processing element, called an artificial neuron
The abstract mathematical description of an artificial neuron