Fitting Parameters on Quantum Weightless Neuron Dynamics

A parametric analysis of a quantum neuron node dynamics is proposed using an output qubit extraction protocol employed in previous works. The proposed classification method is composed of 5 different types of dynamics which explain the parameter changing behavior. The initial conditions analysis for each dynamics type is investigated. This parametric analysis gives a better understanding of the dynamics suggesting how fine-tune the system parameters can influence the system expected behaviour allowing e.g. For applications in patten recognition and information retrieval.