Tutorial series on brain-inspired computing - Part 5: Statistical mechanics of communication and computation

被引:0
|
作者
Kabashima, Yoshiyuki [1 ]
机构
[1] Tokyo Inst Technol, Yokohama, Kanagawa 2268502, Japan
关键词
mean field methods; replica method; error correcting codes; public key cryptosystem; SAT/UNSAT transition;
D O I
10.1007/BF03037401
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
Statistical mechanics (SM) is a branch of theoretical physics that explores cooperative phenomena observed in many body systems. For a long time, applications of SM were limited to material objects such as gases, liquids, metals, magnets, and semi-conductors. However, about a decade ago, concepts and methods developed for SM began to be actively applied to problems in information science. These applications have provided various ground-breaking results, particularly in the fields of communication and computation. Such activities are still ongoing, resulting in the development of a novel cross-disciplinary research field between the natural and the information sciences. In this review article, we show why and how SM can be utilized in information science, illustrating its use by means of three applications: error correcting codes, a public key cryptosystem, and analysis of a decision problem.
引用
收藏
页码:403 / 420
页数:18
相关论文
共 50 条
  • [41] Brain-inspired computing with fluidic iontronic nanochannels
    Kamsma, Tim M.
    Kim, Jaehyun
    Kim, Kyungjun
    Boon, Willem Q.
    Spitoni, Cristian
    Park, Jungyul
    van Roij, Rene
    [J]. PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA, 2024, 121 (18)
  • [42] Brain-inspired computing needs a master plan
    A. Mehonic
    A. J. Kenyon
    [J]. Nature, 2022, 604 : 255 - 260
  • [43] Materials challenges and opportunities for brain-inspired computing
    Zhao, Y. D.
    Kang, J. F.
    Ielmini, D.
    [J]. MRS BULLETIN, 2021, 46 (10) : 978 - 986
  • [44] Memristive Devices and Networks for Brain-Inspired Computing
    Zhang, Teng
    Yang, Ke
    Xu, Xiaoyan
    Cai, Yimao
    Yang, Yuchao
    Huang, Ru
    [J]. PHYSICA STATUS SOLIDI-RAPID RESEARCH LETTERS, 2019, 13 (08):
  • [45] A review of basic software for brain-inspired computing
    Peng Qu
    Le Yang
    Weimin Zheng
    Youhui Zhang
    [J]. CCF Transactions on High Performance Computing, 2022, 4 : 34 - 42
  • [46] Emerging Optoelectronic Devices for Brain-Inspired Computing
    Hu, Lingxiang
    Zhuge, Xia
    Wang, Jingrui
    Wei, Xianhua
    Zhang, Li
    Chai, Yang
    Xue, Xiaoyong
    Ye, Zhizhen
    Zhuge, Fei
    [J]. ADVANCED ELECTRONIC MATERIALS, 2024,
  • [47] A review of basic software for brain-inspired computing
    Qu, Peng
    Yang, Le
    Zheng, Weimin
    Zhang, Youhui
    [J]. CCF TRANSACTIONS ON HIGH PERFORMANCE COMPUTING, 2022, 4 (01) : 34 - 42
  • [48] Fulfilling Brain-inspired Hyperdimensional Computing with In-memory Computing
    Rahimi, Abbas
    Le Gallo, Manuel
    Abu Sebastian
    [J]. ERCIM NEWS, 2021, (125): : 28 - 30
  • [49] A Brain-Inspired In-Memory Computing System for Neuronal Communication via Memristive Circuits
    Ji, Xiaoyue
    Dong, Zhekang
    Lai, Chun Sing
    Qi, Donglian
    [J]. IEEE COMMUNICATIONS MAGAZINE, 2022, 60 (01) : 100 - 106
  • [50] Brain-inspired Learning drives Advances in Neuromorphic Computing
    Ahmad, Nasir
    Rueckauer, Bodo
    van Gerven, Marcel
    [J]. ERCIM NEWS, 2021, (125): : 24 - 25