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Method and apparatus that carries out self-organizing of internal states of a state transition prediction model, and obtains a maximum likelihood sequence

机译:进行状态转移预测模型的内部状态的自组织并获得最大似然序列的方法和装置

摘要

An information processing device includes a model learning unit that carries out learning for self-organization of internal states of a state transition prediction model which is a learning model having internal states, a transition model of the internal states, and an observation model where observed values are generated from the internal states, by using first time series data, wherein the model learning unit learns the observation model of the state transition prediction model after the learning using the first time series data, by fixing the transition model and using second time series data different from the first time series data, thereby obtaining the state transition prediction model having a first observation model where each sample value of the first time series data is observed and a second observation model where each sample value of the second time series data is observed.
机译:信息处理装置包括模型学习单元,该模型学习单元进行用于状态转变预测模型的内部状态的自组织的学习,该状态转变预测模型是具有内部状态的学习模型,内部状态的转变模型和其中观察值的观察模型通过使用第一时间序列数据从内部状态生成数据,其中模型学习单元在学习之后使用第一时间序列数据,通过固定过渡模型并使用第二时间序列数据来学习状态转变预测模型的观察模型。与第一时间序列数据不同,从而获得具有第一观察模型和第二观察模型的状态转变预测模型,其中第一观察模型观察第一时间序列数据的每个样本值,第二观察模型观察第二时间序列数据的每个样本值。

著录项

  • 公开/公告号US8447708B2

    专利类型

  • 公开/公告日2013-05-21

    原文格式PDF

  • 申请/专利权人 KOHTARO SABE;

    申请/专利号US20100915616

  • 发明设计人 KOHTARO SABE;

    申请日2010-10-29

  • 分类号G06F11;

  • 国家 US

  • 入库时间 2022-08-21 16:45:04

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