A Fuzzy Learning model for retrieving and learning information in Visual Working brain Memory mechanism

In this investigation, the idea of Visual Working Memory (VWM) mechanism modeling based on versatile fuzzy method; Active Learning method, is presented. Visual information process; retrieving and learning rely on the use of Ink Drop Spread (IDS) and Center of Gravity (COG) as spatial density convergence operators. IDS modeling is characterized by processing that uses intuitive pattern information instead of complex formulas, and it is capable of stable and fast convergence. Furthermore, because it approves that distortion in retrieving irrelative data is adaptive to avoid storing lots of repetitive external information in daily visualization. Subsequently, this distortion is analyzed via two versions of ALM. Finally, results pursue the hypothesis in which the simulation of concepts of VWM performance; dynamic information retrieval as compensation, storing and active learning, is presented.