This paper investigates the problem of channel equalization in digital cellular radio (DCR). These channels are affected by inter symbol interference (ISI) with non-linearity in presence of additive white Gaussian noise (AWGN). Here we propose a computationally efficient neuro- fuzzy system based equalizer for use in communication channels with these anamolies. This equalizer performs close to the optimum maximum a-posteriori probability (MAP) equalizer with a substantial reduction in computational complexity and can be trained with supervised scalar clustering algorithm. These features can make the equalizer very suitable for mobile communication applications. Simulation studies indicate that this equalizer performs close to optimal equalizer.
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