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This paper deals with methods for multiple position room response equalization. Differently from a well-known technique working in the time domain and based on fuzzy c-means clustering, in the proposed approach most of the operations are performed in the frequency domain and, in particular, the fuzzy c-means clustering is applied to the room magnitude responses at different positions. It is shown that working in the frequency domain allows us to obtain equalization performances at least similar to those of the time domain approach with a strongly reduced computational complexity. In addition, different techniques that can replace the fuzzy c-means clustering algorithm in the derivation of the prototype room response equalizer, with additional reduction of the number of operations, are discussed. Finally, the results of three sets of experiments are used to illustrate the performance, the robustness and the quality of the proposed room response equalization method using alternative prototype design strategies applied to different environments.