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Introduce new Neural network architecture for efficient decision making without significant loss of representational capability • Use of Difference of Convex (DC) programming in decision making involving neural networks • DC optimization produces better result at each iteration and guarantees convergence with the proposed neural network architecture• Optimization problem at each step reduces to Linear Programming problem with the proposed network architecture• Illustration of advantages of this neural network structure through several case studies

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