公开(公告)号：US08560467B2

公开(公告)日：2013-10-15

申请号：US12839321

申请日：2010-07-19

申请人： Masato Ito ,  Kohtaro Sabe ,  Hirotaka Suzuki ,  Jun Yokono ,  Kazumi Aoyama ,  Takashi Hasuo

发明人： Masato Ito ,  Kohtaro Sabe ,  Hirotaka Suzuki ,  Jun Yokono ,  Kazumi Aoyama ,  Takashi Hasuo

IPC分类号： G06F15/18

CPC分类号： G06K9/00335 ,  G06K9/00664 ,  G06K9/00778

摘要： A data processing apparatus includes an obtaining unit for obtaining time-series data, an activity model learning unit for learning an activity model representing a user activity state as a stochastic state transition model from the obtained time-series data, a recognition unit for recognizing a current user activity state by using the learned activity model, and a prediction unit for predicting a user activity state after a predetermined time elapses from a current time from the recognized current user activity state, wherein the prediction unit predicts the user activity state as an occurrence probability, and calculates the occurrence probabilities of the respective states on the basis of the state transition probability of the stochastic state transition model to predict the user activity state, while it is presumed that observation probabilities of the respective states at the respective times of the stochastic state transition model are an equal probability.

摘要翻译： 数据处理装置包括：获取单元，用于获取时间序列数据;活动模型学习单元，用于从所获得的时间序列数据中学习表示用户活动状态的活动模型作为随机状态转换模型;识别单元，用于识别 通过使用所学习的活动模型的当前用户活动状态，以及预测单元，用于在从所识别的当前用户活动状态起从当前时间经过预定时间之后预测用户活动状态，其中，所述预测单元将所述用户活动状态预测为发生 概率，并且基于随机状态转换模型的状态转移概率来计算各个状态的发生概率以预测用户活动状态，同时假设在随机的各个时间的各个状态的观察概率 状态转换模型是相等的概率。

公开(公告)号：US20110029465A1

公开(公告)日：2011-02-03

申请号：US12839321

申请日：2010-07-19

申请人： Masato ITO ,  Kohtaro Sabe ,  Hirotaka Suzuki ,  Jun Yokono ,  Kazumi Aoyama ,  Takashi Hasuo

发明人： Masato ITO ,  Kohtaro Sabe ,  Hirotaka Suzuki ,  Jun Yokono ,  Kazumi Aoyama ,  Takashi Hasuo

IPC分类号： G06F15/18

CPC分类号： G06K9/00335 ,  G06K9/00664 ,  G06K9/00778

摘要： A data processing apparatus includes an obtaining unit configured to obtain time-series data from a wearable sensor, an activity model learning unit configured to learn an activity model representing a user activity state as a stochastic state transition model from the obtained time-series data, a recognition unit configured to recognize a current user activity state by using the activity model of the user obtained by the activity model learning unit, and a prediction unit configured to predict a user activity state after a predetermined time elapses from a current time from the current user activity state recognized by the recognition unit.

摘要翻译： 数据处理装置包括获取单元，被配置为从可穿戴传感器获取时间序列数据;活动模型学习单元，被配置为从所获得的时间序列数据中学习表示用户活动状态的活动模型作为随机状态转换模型， 识别单元，被配置为通过使用由活动模型学习单元获得的用户的活动模型来识别当前用户活动状态;以及预测单元，被配置为在从当前的当前时间经过预定时间之后预测用户活动状态 用户活动状态由识别单元识别。

公开(公告)号：US07783585B2

公开(公告)日：2010-08-24

申请号：US11697238

申请日：2007-04-05

申请人： Kohtaro Sabe ,  Kazumi Aoyama ,  Jun Yokono ,  Kenichi Hidai ,  Kuniaki Noda

发明人： Kohtaro Sabe ,  Kazumi Aoyama ,  Jun Yokono ,  Kenichi Hidai ,  Kuniaki Noda

IPC分类号： G06E1/00 ,  G06E3/00 ,  G06F15/18 ,  G06G7/00

CPC分类号： G06F15/18 ,  G06N3/0454 ,  G06N3/088

摘要： A data processing device for processing time-sequence data includes a learning unit for performing self-organizing learning of a SOM (self-organization map) making up a hierarchical SOM in which a plurality of SOMs are connected so as to construct a hierarchical structure, using, as SOM input data which is input to the SOM, a time-sequence of node information representing a winning node of a lower-order SOM which is at a lower hierarchical level from the SOM.

摘要翻译： 一种用于处理时间序列数据的数据处理装置，包括：学习单元，用于执行构成其中连接有多个SOM的层次化SOM的SOM（自组织图）的自组织学习，以构建层次结构， 使用作为输入到SOM的SOM输入数据，表示代表来自SOM的较低层级的低阶SOM的获胜节点的节点信息的时间序列。

公开(公告)号：US20070250461A1

公开(公告)日：2007-10-25

申请号：US11697238

申请日：2007-04-05

申请人： Kohtaro Sabe ,  Kazumi Aoyama ,  Jun Yokono ,  Kenichi Hidai ,  Kuniaki Noda

发明人： Kohtaro Sabe ,  Kazumi Aoyama ,  Jun Yokono ,  Kenichi Hidai ,  Kuniaki Noda

IPC分类号： G06F15/18

CPC分类号： G06F15/18 ,  G06N3/0454 ,  G06N3/088

摘要： A data processing device for processing time-sequence data includes a learning unit for performing self-organizing learning of a SOM (self-organization map) making up a hierarchical SOM in which a plurality of SOMs are connected so as to construct a hierarchical structure, using, as SOM input data which is input to the SOM, a time-sequence of node information representing a winning node of a lower-order SOM which is at a lower hierarchical level from the SOM.

摘要翻译： 一种用于处理时间序列数据的数据处理装置，包括：学习单元，用于执行构成其中连接有多个SOM的层次化SOM的SOM（自组织图）的自组织学习，以构建层次结构， 使用作为输入到SOM的SOM输入数据，表示代表来自SOM的较低层级的低阶SOM的获胜节点的节点信息的时间序列。

公开(公告)号：US20070280006A1

公开(公告)日：2007-12-06

申请号：US11732644

申请日：2007-04-04

申请人： Kazumi Aoyama ,  Kohtaro Sabe ,  Hideki Shimomura

发明人： Kazumi Aoyama ,  Kohtaro Sabe ,  Hideki Shimomura

IPC分类号： G11C7/10

CPC分类号： G06F17/30551 ,  G06K9/0057 ,  G06K9/6251

摘要： A data processing device for processing time-sequence data includes a data extracting unit operable to extract time-sequence data for a predetermined time unit from time-sequence data; and a processing unit operable to obtain scores for nodes of an SOM configured from multiple nodes provided with a spatial array configuration, the scores showing applicability to time-sequence data for a predetermined time unit thereof, wherein the node with the best score thereof is determined to be the winning node which is the node most applicable; wherein the processing unit obtains scores as to the time-sequence data for one predetermined time unit, regarding a distance-restricted node wherein distance from the winning node as to the time-sequence for a predetermined time unit immediately preceding the time-sequence data of one predetermined time unit is within a predetermined distance; and wherein the distance-restricted node with the best the score is determined to be the winning node thereof.

摘要翻译： 一种用于处理时间序列数据的数据处理装置，包括数据提取单元，用于从时间序列数据中提取预定时间单位的时间序列数据; 以及处理单元，其可操作以获得由具有空间阵列配置的多个节点配置的SOM的节点的分数，所述分数显示对于其预定时间单位的时间序列数据的适用性，其中确定具有最佳分数的节点 作为最适用节点的获胜节点; 其中处理单元获得关于一个预定时间单位的时间序列数据的分数，关于距离受限节点的距离限制节点，其中距离获胜节点的距离与时间序列的时间顺序紧邻在时间序列数据之前的预定时间单位 一个预定时间单位在预定距离内; 并且其中具有最佳分数的距离限制节点被确定为其获胜节点。

公开(公告)号：US07725412B2

公开(公告)日：2010-05-25

申请号：US11732644

申请日：2007-04-04

申请人： Kazumi Aoyama ,  Kohtaro Sabe ,  Hideki Shimomura

发明人： Kazumi Aoyama ,  Kohtaro Sabe ,  Hideki Shimomura

IPC分类号： G06F15/00

CPC分类号： G06F17/30551 ,  G06K9/0057 ,  G06K9/6251

摘要： A data processing device for processing time-sequence data includes a data extracting unit extracting time-sequence data for a predetermined time unit from time-sequence data; and a processing unit obtaining scores for nodes of an SOM configured from multiple nodes provided with a spatial array configuration, the scores showing applicability to time-sequence data for a predetermined time unit thereof. The node with the best score is determined to be the winning node which is the node most applicable. The processing unit obtains scores as to the time-sequence data for one predetermined time unit, regarding a distance-restricted node wherein distance from the winning node as to the time-sequence for a predetermined time unit immediately preceding the time-sequence data of one predetermined time unit is within a predetermined distance. The distance-restricted node with the best the score is determined to be the winning node.

摘要翻译： 一种用于处理时间序列数据的数据处理装置，包括数据提取单元，从时间序列数据提取预定时间单位的时间序列数据; 以及处理单元，其获得由具有空间阵列配置的多个节点配置的SOM的节点，所述分数显示对于其预定时间单位的时间序列数据的适用性。 具有最佳分数的节点被确定为作为最适用节点的获胜节点。 处理单元获得关于一个预定时间单位的时间序列数据的分数，关于距离限制节点的距离限制节点，其中距离胜利节点的距离与紧接在一个的时间序列数据之前的预定时间单位的时间序列 预定时间单位在预定距离内。 得分最高的距离限制节点被确定为获胜节点。

公开(公告)号：US20090299933A1

公开(公告)日：2009-12-03

申请号：US12413004

申请日：2009-03-27

申请人： Kazumi Aoyama ,  Masato Ito ,  Kuniaki Noda

发明人： Kazumi Aoyama ,  Masato Ito ,  Kuniaki Noda

IPC分类号： G06N5/02 ,  G06F15/18

CPC分类号： G06N3/049

摘要： A data processing apparatus includes: predicting means for calculating a prediction value of time series data with respect to input of the time series data using a prediction model for predicting the time series data; determining means for determining a target value of the time series data on the basis of the prediction value of the time series data; error calculating means for calculating an error of the prediction value relative to the target value; and retrieving means for retrieving error reduction data as input of the time series data to the prediction model for reducing the error of the prediction value.

摘要翻译： 数据处理装置包括：预测装置，用于使用用于预测时间序列数据的预测模型来计算关于时间序列数据的输入的时间序列数据的预测值; 确定装置，用于根据时间序列数据的预测值确定时间序列数据的目标值; 误差计算装置，用于计算预测值相对于目标值的误差; 以及检索装置，用于将所述时间序列数据的输入作为输入的误差减少数据提取到所述预测模型，以减少所述预测值的误差。

公开(公告)号：US08290887B2

公开(公告)日：2012-10-16

申请号：US12498760

申请日：2009-07-07

申请人： Masato Ito ,  Kazumi Aoyama ,  Kuniaki Noda

发明人： Masato Ito ,  Kazumi Aoyama ,  Kuniaki Noda

IPC分类号： G06G7/00

CPC分类号： G06N3/08 ,  G06N3/0454

摘要： A device for implementing a pattern learning model, the device including a plurality of learning modules, each of which performs update learning to update a plurality of model parameters of the pattern learning model that learns a pattern using input data. The device further including a model parameter sharing means for causing two or more learning modules from among the plurality of learning modules to share the model parameters; and a classification means for classifying the plurality of learning modules on the basis of the plurality of model parameters of each of the learning modules after the update learning.

摘要翻译： 一种用于实现模式学习模型的装置，该装置包括多个学习模块，每个学习模块执行更新学习以更新使用输入数据学习模式的模式学习模型的多个模型参数。 所述设备还包括：模型参数共享装置，用于使所述多个学习模块中的两个或更多个学习模块共享所述模型参数; 以及分类装置，用于在更新学习之后，基于每个学习模块的多个模型参数来分类多个学习模块。

公开(公告)号：US20100010949A1

公开(公告)日：2010-01-14

申请号：US12498760

申请日：2009-07-07

申请人： Masato Ito ,  Kazumi Aoyama ,  Kuniaki Noda

发明人： Masato Ito ,  Kazumi Aoyama ,  Kuniaki Noda

IPC分类号： G06F15/18 ,  G06N3/08

CPC分类号： G06N3/08 ,  G06N3/0454

摘要： A learning device includes: a plurality of learning modules, each of which performs update learning to update a plurality of model parameters of a pattern learning model that learns a pattern using input data; model parameter sharing means for causing two or more learning modules from among the plurality of learning modules to share the model parameters; and classification means for classifying the plurality of learning modules on the basis of the plurality of model parameters of each of the learning modules after the update learning.

摘要翻译： 学习装置包括：多个学习模块，每个学习模块执行更新学习以更新使用输入数据学习模式的模式学习模型的多个模型参数; 模型参数共享装置，用于使所述多个学习模块中的两个或更多学习模块共享所述模型参数; 以及分类装置，用于在更新学习之后，基于每个学习模块的多个模型参数来分类多个学习模块。

公开(公告)号：US08306930B2

公开(公告)日：2012-11-06

申请号：US12498718

申请日：2009-07-07

申请人： Masato Ito ,  Kazumi Aoyama ,  Kuniaki Noda

发明人： Masato Ito ,  Kazumi Aoyama ,  Kuniaki Noda

IPC分类号： G06G7/00

CPC分类号： G06N3/0454 ,  G06N3/08

摘要： A learning device, learning method, and program for learning a pattern are disclosed. A learning device includes: a plurality of learning modules, each of which performs update learning to update a plurality of model parameters of a pattern learning model that learns a pattern using input data; model parameter sharing means for causing two or more learning modules from among the plurality of learning modules to share the model parameters; and sharing strength updating means for updating sharing strengths between the learning modules so as to minimize learning errors when the plurality of model parameters are updated by the update learning.

摘要翻译： 公开了一种用于学习图案的学习装置，学习方法和程序。 学习装置包括：多个学习模块，每个学习模块执行更新学习以更新使用输入数据学习模式的模式学习模型的多个模型参数; 模型参数共享装置，用于使所述多个学习模块中的两个或更多学习模块共享所述模型参数; 以及共享强度更新装置，用于更新所述学习模块之间的共享强度，以便当所述更新学习更新所述多个模型参数时，最小化学习错误。