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In reference 19, a so-called general tensor discriminant analysis (GTDA) algorithm is proposed by maximizing a scatter difference criterion, and it is used as a preprocessing step in tensorial gait data classi cation [19]. All these methodologies are based on the tensor-to-tensor projection (TTP). The so-called Tensor Rank-one Discriminant Analysis (TR1DA) algorithm [27, 28], which uses the scatter difference criterion, obtains a number of rank-one projections from the repeatedly calculated residues of the original tensor data and it can be viewed as a tensor-to-vector projection (TVP). This greedy approach is a heuristic method originally proposed in reference 29 for tensor approximation. In reference 30, an uncorrelated multilinear discriminant analysis (UMLDA) approach is proposed to extract uncorrelated features through TVP. 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