Analysis of FFANN Used for Pattern Recognition

FFANN is a powerfull computational model used in various vital applications, these applications require exccelent performane by minimizing the mean square error between the target and the calculating output achieving a high value of recognition ratio. Two methods of creating FFANN model will be introduced and analysized, it will be shown how the programming model of FFANN will increase the recognition ratio and how it is easy to build, train and test this model, this model will be adjustable to suit any input data set and target.