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Huge Complexity Reduction of Non-singleton Based Generalized Neural Network in Controlling an AGV Steering System

During the past few years, efficient singular value based complexity reduction tools have been developed to fuzzy logic techniques. Using these techniques, this paper presents the practical complexity reduction of a huge non-singleton based generalized neural network. This algorithm proposed in this paper is capable of reducing the generalized network by its divided parts to fit the operation memory available for singular value decomposition than finally reconstructs the reduced network. An example of automatically guided vehicle (AGV) steering system is presented in this paper also.