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This study considers robust filtering problems for uncertain two dimensional (2-D) discrete systems in nonlinear fractional transformation (NFT) representations. Like one-dimensional (1-D) systems, the NFT in this paper serves to complement the linear fractional transformation (LFT). Linear matrix inequality (LMI) formulations are given to analyze as well as synthesize robust filters. Numerical examples show the advantage of the NFT over the LFT in terms of not only computational savings but also substantial performance gains and verify the efficiency of the proposed techniques.