Literature DB >> 28113730

Probe Machine.

Jin Xu.   

Abstract

In this paper, we present a novel computing model, called probe machine (PM). Unlike the turing machine (TM), PM is a fully parallel computing model in the sense that it can simultaneously process multiple pairs of data, rather than sequentially process every pair of linearly adjacent data. We establish the mathematical model of PM as a nine-tuple consisting of data library, probe library, data controller, probe controller, probe operation, computing platform, detector, true solution storage, and residue collector. We analyze the computation capability of the PM model, and in particular, we show that TM is a special case of PM. We revisit two NP-complete problems, i.e., the graph coloring and Hamilton cycle problems, and devise two algorithms on basis of the established PM model, which can enumerate all solutions to each of these problems by only one probe operation. Furthermore, we show that PM can be implemented by leveraging the nano-DNA probe technologies. The computational power of an electronic computer based on TM is known far more than that of the human brain. A question naturally arises: will a future computer based on PM outperform the human brain in more ways beyond the computational power?

Entities:  

Year:  2016        PMID: 28113730     DOI: 10.1109/TNNLS.2016.2555845

Source DB:  PubMed          Journal:  IEEE Trans Neural Netw Learn Syst        ISSN: 2162-237X            Impact factor:   10.451


  2 in total

1.  An algorithm based on positive and negative links for community detection in signed networks.

Authors:  Yansen Su; Bangju Wang; Fan Cheng; Lei Zhang; Xingyi Zhang; Linqiang Pan
Journal:  Sci Rep       Date:  2017-09-07       Impact factor: 4.379

2.  Small Universal Bacteria and Plasmid Computing Systems.

Authors:  Xun Wang; Pan Zheng; Tongmao Ma; Tao Song
Journal:  Molecules       Date:  2018-05-29       Impact factor: 4.411

  2 in total

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