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First, a fuzzy system based on if-then rules and with parametric consequences is recalled. Then, it is shown that the global and local ?-insensitive learning of the above fuzzy system may be presented as a combination of both an ?-insensitive gradient method and solving a system of linear inequalities. Examples are given of using the introduced method to design fuzzy models of real-life data.