Titlebook: DNA Computing; 7th International Wo Nata?a Jonoska,Nadrian C. Seeman Conference proceedings 2002 Springer-Verlag Berlin Heidelberg 2002 Bio

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書(shū)目名稱DNA Computing影響因子(影響力)




書(shū)目名稱DNA Computing影響因子(影響力)學(xué)科排名




書(shū)目名稱DNA Computing網(wǎng)絡(luò)公開(kāi)度




書(shū)目名稱DNA Computing網(wǎng)絡(luò)公開(kāi)度學(xué)科排名




書(shū)目名稱DNA Computing被引頻次




書(shū)目名稱DNA Computing被引頻次學(xué)科排名




書(shū)目名稱DNA Computing年度引用




書(shū)目名稱DNA Computing年度引用學(xué)科排名




書(shū)目名稱DNA Computing讀者反饋




書(shū)目名稱DNA Computing讀者反饋學(xué)科排名

安心地散步

https://doi.org/10.1007/978-3-322-97044-2e chemical reactions, it seems to be clearly important to optimize each reaction protocol in order to improve the reliability of computing. Moreover, the purpose of the reaction in DNA Computing crosses variably. We consider that the optimization of reaction protocol according to each purpose will b

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mechanism

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爵士樂(lè)

Arbeits- und Organisationspsychologie number of DNA strands in the test tube and a probabilistic logical inference based on the probabilistic interpretation. Second, in order for the DNA-based learning algorithm [.] to be robust for errors in the data, we implement the weighted majority algorithm [.] on DNA computers, called . (DNAMA),

MINT

Arbeits- und Organisationspsychologie) to wait your turn, (2) to default to the most conservative course, (3) to probabilistically override the default in some cases, and (4) to learn from payoffs. Two players each use an independent population of strategies that adapt and learn from their experiences in competition.

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