公开(公告)号：US20150046135A1

公开(公告)日：2015-02-12

申请号：US14387307

申请日：2013-03-29

Applicant: Sony Corporation

Inventor： Masato Ito ,  Kohtaro Sabe

IPC: G06F17/18 ,  G06N99/00

Abstract: Apparatus, methods and programs for estimating a parameter for modeling a time series signal with stochastic dynamics model, A method for obtaining data representing the mixed signals of two or more time series signals; estimating a parameter for modeling a time series signal with stochastic dynamics model. The present technology relates to a data processing apparatus, a data processing method, and a program.

Abstract translation: 一种用于估计用于使用随机动力学模型建模时间序列信号的参数的装置，方法和程序。一种用于获得表示两个或更多个时间序列信号的混合信号的数据的方法; 估计用随机动力学模型建模时间序列信号的参数。 本技术涉及数据处理装置，数据处理方法和程序。

公开(公告)号：US10452986B2

公开(公告)日：2019-10-22

申请号：US14387307

申请日：2013-03-29

Applicant: Sony Corporation

Inventor： Masato Ito ,  Kohtaro Sabe

IPC: G06F17/50 ,  G06N7/00 ,  G06N20/00 ,  G06F17/10 ,  G06Q50/06 ,  G06Q10/06 ,  G06F17/18 ,  G01D4/00 ,  G01R21/133

Abstract: Apparatus, methods and programs for estimating a parameter for modeling a time series signal with stochastic dynamics model, A method for obtaining data representing the mixed signals of two or more time series signals; estimating a parameter for modeling a time series signal with stochastic dynamics model. The present technology relates to a data processing apparatus, a data processing method, and a program.

公开(公告)号：US20150112891A1

公开(公告)日：2015-04-23

申请号：US14398586

申请日：2013-06-05

Applicant: SONY CORPORATION

Inventor： Yusuke Watanabe ,  Masato Ito ,  Masahiro Tamori

IPC: G06N7/00 ,  G06N5/04

CPC classification number: G06N7/005 ,  G06N5/048 ,  G06N20/00

Abstract: The present technique relates to an information processor, an information processing method, and a program by which an objective variable value is efficiently and highly precisely estimated.A log acquisition unit acquires objective time-series data corresponding to the objective variable to be estimated, and a plurality of pieces of explanatory time-series data being time-series data corresponding to a plurality of explanatory variables explaining the objective variable. A model parameter update unit learns a parameter of a probability model using the acquired objective time-series data and plurality of pieces of explanatory time-series data. A log selection unit selects, based on the parameter of the probability model having been obtained by the learning, the explanatory variable corresponding to the explanatory time-series data acquired by the log acquisition unit. An estimation unit estimates the objective variable value, using the plurality of pieces of explanatory time-series data having been acquired by the log acquisition unit based on a selection result of the selection unit. The present technique may be applied to for example an information processor for estimating device power consumption.

Abstract translation: 本技术涉及一种信息处理器，信息处理方法以及高效高精度地估计客观变量值的程序。 日志获取单元获取与要估计的目标变量相对应的目标时间序列数据，以及多个说明时间序列数据，其是与解释目标变量的多个解释变量对应的时间序列数据。 模型参数更新单元使用所获取的目标时间序列数据和多条说明时间序列数据来学习概率模型的参数。 日志选择单元基于通过学习获得的概率模型的参数，选择与由日志获取单元获取的解释时间序列数据相对应的解释变量。 使用已经由日志获取单元基于选择单元的选择结果获取的多条解释性时间序列数据来估计目标变量值。 本技术可以应用于例如用于估计设备功耗的信息处理器。