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In this paper we use computational intelligence numerical optimization techniques to design optimum non-linear phase finite impulse response digital filters. The filter magnitude and group delay approximation will be presented as a classical approximation problem, where a non-linear function of several variables must be minimized. Results will be presented and compared with three different numerical optimization techniques developed, including Genetic algorithms, Simulated Annealing and Particle Swarm Optimization. Additionally, results are compared with a current used design technique, an unconstrained quasi-Newton algorithm.