Advances in Neuro-Information Processing

Integrative evolving connectionist systems (iECOS) integrate principles from different levels of information processing in the brain, including cognitive-, neuronal-, genetic- and quantum, in their dynamic interaction over time. The paper introduces a new framework of iECOS called integrative probabilistic evolving spiking neural networks (ipSNN) that incorporate probability learning parameters. ipSNN utilize a quantum inspired evolutionary optimization algorithm to optimize the probability parameters as these algorithms belong to the class of estimation of distribution algorithms (EDA). Both spikes and input features in ipESNN are represented as quantum bits being in a superposition of two states (1 and 0) defined by a probability density function. This representation allows for the state...