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The Cerebellar Model Articulation Controller (CMAC) neural network is an associative memory that is biologically inspired by the cerebellum, which is found in the brains of animals. The standard CMAC uses the least mean squares algorithm (LMS) to train the weights. Recently, the recursive least squares (RLS) algorithm was proposed as a superior algorithm for training the CMAC online as it can converge in one epoch, and does not require tuning of a learning rate. However, the RLS algorithm wasdoi:10.7763/ijmlc.2012.v2.172 fatcat:kagdcjxbinddpielj7jhscz6ie