Artificial neural networks (ANNs) model the relationship between a set of input signals and output signals using a model derived from a replica of the biological brain, which responds to stimuli from its sensory inputs. The human brain consists of about 90 billion neurons, with around 1 trillion connections between them; ANN methods try to model problems using interconnected artificial neurons (or nodes) to solve machine learning problems.
As we know, ANNs have taken inspiration from the biological neuron. We will spend some time understanding how biological neurons work. Incoming signals are received by the cell's dendrites through a biochemical process that allows the impulses to be weighted according to their relative importance. As the cell body begins to accumulate the incoming signals, a threshold is reached, at which the cell fires and the output signal is then transmitted via an electrochemical process down the axon. At the axon terminal, an electric...
