Artificial Neural Networks (ANNs)
In this work we evaluate ANNs as they are a collaborative network which is easy to design and evaluate. ANNs leverage very simple computations to develop incredibly sophisticated capabilities.
A common simple example of an ANN is the multilayer perceptron, which is an weighted directed acyclic computational graph. Each edge is weight corresponds to the importance of the activation of the node it originates from to the node it enters. Non-linear functions filter the activation to give the NN its function approximation capability. An example of a multilayer perceptron is as follows: