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Based on state projection method with two-step operations, this paper deals with the model reduction problem by analyzing the information descriptions of system states. Our basic idea in obtaining the reduced-order models is to minimize the information loss or the conditional information loss caused by truncation by eliminating the state variables with the(More)
BACKGROUND Human telomerase reverse transcriptase (hTERT) has become an ideal target for development of anticancer therapy. Small interfering RNAs (siRNAs) are very powerful reagents for gene silencing and show promise for cancer gene therapy. However, only a small number of siRNAs have been demonstrated to be effective. For gene therapy targeting hTERT, it(More)
Linearized Bregman algorithm is effective on solving l1-minimization problem, but its parameter's selection must rely on prior information. In order to ameliorate this weakness, we proposed a new algorithm in this paper, which combines the proximal point algorithm and the linearized Bregman iterative method. In the second part of the paper, the proposed(More)
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