Numerical P systems are a class of P systems inspired both from the structure of living cells and from economics. In this work, we further investigate the generative capacity of numerical P systems as language generators. The families of languages generated by non-enzymatic, by enzymatic, and by purely enzymatic (all programs are enzymatic) numerical P systems working in the sequential mode are compared with the language families in the Chomsky hierarchy. Especially, a characterization of recursively enumerable languages is obtained by using purely enzymatic numerical P systems working in the sequential mode.
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The objective of the present study is to propose a new sequential projective factorization approach for recovering the structure and motion. In contrast to the previous sequential factorization methods or nonlinear filter methods, it starts with the first two images and the accurate result can be obtained even for the first image pair without considering provision of a reliable initial estimation. In each recursive step, the infinite sequences can be effectively handled while keeping the size of the factorization matrix unchanged. The experimental data in the paper show that sufficient accuracy can be attained with absence of noise.
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