MULTIDIMENSIONAL RECURSIVE LEARNING PROCESS AND SYSTEM USED TO DISCOVER COMPLEX DYADIC OR MULTIPLE COUNTERPARTY RELATIONSHIPS

• 1. 用于发现复杂两对手方或多对手方关系的多维递归学习过程及系统 [P] . 中国专利： CN106164896A . 2016-11-23
• 2. 用于发现对手方关系的多维递归方法及系统 [P] . 中国专利： CN106164896B . 2020.03.03
• 3. A MULTIDIMENSIONAL RECURSIVE LEARNING PROCESS AND SYSTEM USED TO DISCOVER COMPLEX DYADIC OR MULTIPLE COUNTERPARTY RELATIONSHIPS [P] . 韩国专利： KR101953190B1 . 2019-06-17

  机译： 用于发现复杂动态或多对等关系的多维递归学习过程和系统

• 4. A multidimensional recursive learning process and system used to discover complex dyadic or multiple counterparty relationships [P] . AU2014374029B2 . 2018-04-26

  机译： 用于发现复杂的二元或多个交易对手关系的多维递归学习过程和系统

• 5. A MULTIDIMENSIONAL RECURSIVE LEARNING PROCESS AND SYSTEM USED TO DISCOVER COMPLEX DYADIC OR MULTIPLE COUNTERPARTY RELATIONSHIPS [P] . CA2935281C . 2018-07-31

  机译： 用于发现复杂动态或多对等关系的多维递归学习过程和系统

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• 1. Hierarchical Modeling by Recursive Unsupervised Spectral Clustering and Network Extended Importance Measures to Analyze the Reliability Characteristics of Complex Network Systems [J] . Yiping Fang ,Enrico Zio . 美国运筹学期刊（英文） . 2013,第1期
• 2. Low Complexity Multiuser Detection with Recursively Successive Zero-Forcing and SIC Based on Nullspace for Multiuser MIMO-OFDM System [J] . ZHANG Chengwen ,WANG Bin ,LI Danli . 中国通信 . 2015,第009期
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