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Takagi–Sugeno (T–S) fuzzy system identification provides a reasonable framework for modeling and approximation by decomposition of a nonlinear system into a collection of local linear models. In this paper, we extend the multidimensional output fuzzy rule from the corresponding single-output fuzzy rule with the important difference in the variable definition of output, namely the output of each fuzzy...
This paper tries to exploit the joint group intrinsics in face recognition problem by using sparse representation with multiple features. We claim that different feature vectors of one test face image share the same sparsity pattern at the higher group level, but not necessarily at the lower (inside the group) level. This means that they share the same active groups, but not necessarily the same active...
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