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1.发明授权Apparatus and method for embedding recurrent neural networks into the nodes of a self-organizing map 有权将循环神经网络嵌入到自组织图的节点中的装置和方法公开(公告)号：US07672920B2
公开(公告)日：2010-03-02
申请号：US11699428
申请日：2007-01-30
IPC分类号： G06N5/00
CPC分类号： G06K9/00536 , G06K9/00335 , G06N3/0445 , G06N99/005
摘要： A learning system is provided, which includes network storage means for storing a network including a plurality of nodes, each of which holds a dynamics; and learning means for self-organizationally updating the dynamics of the network on the basis of measured time-series data.
摘要翻译： 提供了一种学习系统，其包括用于存储包括多个节点的网络的网络存储装置，每个节点保持动态; 以及基于测量的时间序列数据自组织地更新网络动态的学习手段。
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公开(公告)号：US20070239644A1
公开(公告)日：2007-10-11
申请号：US11732773
申请日：2007-04-04
IPC分类号： G06N3/00
CPC分类号： G06N99/005 , G06N3/0445 , G06N3/0454 , G06N3/084
摘要： A learning apparatus includes a storage unit configured to store a network formed by a plurality of nodes each holding dynamics; a learning unit configured to learn the dynamics of the network in a self-organizing manner on the basis of observed time-series data; a winner-node determiner configured to determine a winner node, the winner node being a node having dynamics that best match the time-series data; and a weight determiner configured to determine learning weights for the dynamics held by the individual nodes according to distances of the individual nodes from the winner node. The learning unit is configured to learn the dynamics of the network in a self-organizing manner by degrees corresponding to the learning weights.
摘要翻译： 学习装置包括：存储单元，被配置为存储由保持动态的多个节点形成的网络; 学习单元，被配置为基于观察到的时间序列数据以自组织的方式学习网络的动态; 获胜者节点确定器，被配置为确定胜者节点，胜者节点是具有与时间序列数据最佳匹配的动态的节点; 以及权重确定器，被配置为根据各个节点与胜利者节点的距离来确定由各个节点保持的动态的学习权重。 学习单元被配置为以自组织的方式以对应于学习权重的度学习网络的动态。
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3.发明授权公开(公告)号：US07840508B2
公开(公告)日：2010-11-23
申请号：US11732807
申请日：2007-04-04
CPC分类号： G06N3/02
摘要： An information processing apparatus includes a storage unit configured to store a node holding dynamics; an input-weight-coefficient adjuster configured to adjust input-weight coefficients on a dimension-by-dimension basis, the input-weight coefficients being weight coefficients for individual dimensions of input data input to input units of the node, the input data being observed time-series data having a plurality of dimensions; and an output-weight-coefficient adjuster configured to adjust output-weight coefficients on a dimension-by-dimension basis, the output-weight coefficients being weight coefficients for individual dimensions of output data having a plurality of dimensions and output from output units of the node.
摘要翻译： 一种信息处理装置，包括：存储单元，被配置为存储保存动态的节点; 输入权重系数调整器，其被配置为在逐个维度的基础上调整输入权重系数，输入权重系数是输入到节点的输入单元的输入数据的各个维度的权重系数，观察到的输入数据 具有多个维度的时间序列数据; 以及输出权重系数调整器，其被配置为在逐个维度的基础上调整输出权重系数，所述输出权重系数是具有多个维度的输出数据的各个维度的权重系数，并且从所述输出单元的输出单元输出 节点。
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4.发明申请公开(公告)号：US20070239635A1
公开(公告)日：2007-10-11
申请号：US11732807
申请日：2007-04-04
IPC分类号： G06N3/02
CPC分类号： G06N3/02
摘要： An information processing apparatus includes a storage unit configured to store a node holding dynamics; an input-weight-coefficient adjuster configured to adjust input-weight coefficients on a dimension-by-dimension basis, the input-weight coefficients being weight coefficients for individual dimensions of input data input to input units of the node, the input data being observed time-series data having a plurality of dimensions; and an output-weight-coefficient adjuster configured to adjust output-weight coefficients on a dimension-by-dimension basis, the output-weight coefficients being weight coefficients for individual dimensions of output data having a plurality of dimensions and output from output units of the node.
摘要翻译： 一种信息处理装置，包括：存储单元，被配置为存储保存动态的节点; 输入权重系数调整器，其被配置为在逐个维度的基础上调整输入权重系数，输入权重系数是输入到节点的输入单元的输入数据的各个维度的权重系数，观察到的输入数据 具有多个维度的时间序列数据; 以及输出权重系数调整器，其被配置为在逐个维度的基础上调整输出权重系数，所述输出权重系数是具有多个维度的输出数据的各个维度的权重系数，并且从所述输出单元的输出单元输出 节点。
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5.发明授权Learning apparatus, learning method, and program for efficiently learning dynamics 失效学习机器，学习方法和有效学习动态的程序公开(公告)号：US07953683B2
公开(公告)日：2011-05-31
申请号：US11732773
申请日：2007-04-04
CPC分类号： G06N99/005 , G06N3/0445 , G06N3/0454 , G06N3/084
摘要： A learning apparatus includes a storage unit configured to store a network formed by a plurality of nodes each holding dynamics; a learning unit configured to learn the dynamics of the network in a self-organizing manner on the basis of observed time-series data; a winner-node determiner configured to determine a winner node, the winner node being a node having dynamics that best match the time-series data; and a weight determiner configured to determine learning weights for the dynamics held by the individual nodes according to distances of the individual nodes from the winner node. The learning unit is configured to learn the dynamics of the network in a self-organizing manner by degrees corresponding to the learning weights.
摘要翻译： 学习装置包括：存储单元，被配置为存储由保持动态的多个节点形成的网络; 学习单元，被配置为基于观察到的时间序列数据以自组织的方式学习网络的动态; 获胜者节点确定器，被配置为确定胜者节点，胜者节点是具有与时间序列数据最佳匹配的动态的节点; 以及权重确定器，被配置为根据各个节点与胜利者节点的距离来确定由各个节点保持的动态的学习权重。 学习单元被配置为以自组织的方式以对应于学习权重的度学习网络的动态。
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6.发明申请Learning system and method, recognition device and method, creation device and method, recognition and creation device and method, and program 有权学习系统与方法，识别装置及方法，创作装置及方法，识别与创作装置及方法及程序公开(公告)号：US20070185825A1
公开(公告)日：2007-08-09
申请号：US11699428
申请日：2007-01-30
IPC分类号： G06N3/00
CPC分类号： G06K9/00536 , G06K9/00335 , G06N3/0445 , G06N99/005
摘要： A learning system is provided, which includes network storage means for storing a network including a plurality of nodes, each of which holds a dynamics; and learning means for self-organizationally updating the dynamics of the network on the basis of measured time-series data.
摘要翻译： 提供了一种学习系统，其包括用于存储包括多个节点的网络的网络存储装置，每个节点保持动态; 以及基于测量的时间序列数据自组织地更新网络动态的学习手段。
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7.发明授权Information processing apparatus and method, and program for teaching an action to a device in a time-series pattern 失效信息处理装置和方法，以及用于以时间序列模式向装置教导动作的程序公开(公告)号：US07814037B2
公开(公告)日：2010-10-12
申请号：US11397148
申请日：2006-04-04
申请人： Masato Ito , Yukiko Yoshiike , Kuniaki Noda , Jun Tani
发明人： Masato Ito , Yukiko Yoshiike , Kuniaki Noda , Jun Tani
IPC分类号： G05B13/02
CPC分类号： B25J9/161 , G05B2219/36442 , G05B2219/40391 , G06N3/008
摘要： An information processing apparatus including a learning unit that learns a predetermined time-series pattern. An output unit outputs a time-series pattern corresponding to the result of learning by the learning unit. An adjusting unit supplied with a time-series pattern obtained from an action by an action unit on the basis of a time-series pattern supplied from the output unit and external teaching for the action adjusts a time-series pattern supplied from the output unit correspondingly to the input time-series pattern. The learning unit learns the time-series pattern supplied from the output unit and adjusted by the adjusting unit.
摘要翻译： 一种信息处理设备，包括学习单元，该学习单元学习预定的时间序列模式。 输出单元输出与学习单元的学习结果相对应的时间序列模式。 相应地，从由输出单元提供的时间序列模式和由动作的外部教导基于由动作单元的动作获得的时间序列模式的调整单元相应地调整从输出单元提供的时间序列模式 到输入时间序列模式。 学习单元学习从输出单元提供并由调整单元调整的时间序列模式。
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公开(公告)号：US20070239641A1
公开(公告)日：2007-10-11
申请号：US11397148
申请日：2006-04-04
申请人： Masato Ito , Yukiko Yoshiike , Kuniaki Noda , Jun Tani
发明人： Masato Ito , Yukiko Yoshiike , Kuniaki Noda , Jun Tani
CPC分类号： B25J9/161 , G05B2219/36442 , G05B2219/40391 , G06N3/008
摘要： Teaching to a robot for an action on an external object can be made easily and efficiently. According to the present invention, there is provided an information processing apparatus including a learning unit for learning a predetermined time-series pattern, an output unit for outputting a time-series pattern corresponding to the result of learning by the learning unit, and an adjusting unit supplied with a time-series pattern obtained from an action made by an action unit on the basis of a time-series pattern supplied from the output unit and external teaching for the action to adjust a time-series pattern supplied from the output unit correspondingly to the input time-series pattern, the learning unit learning the time-series pattern supplied from the output unit and adjusted by the adjusting unit.
摘要翻译： 可以轻松有效地向机器人教授外部物体上的动作。 根据本发明，提供了一种信息处理设备，包括用于学习预定时间序列模式的学习单元，输出单元，用于输出与学习单元的学习结果相对应的时间序列模式，以及调整 单元被提供有从由动作单元根据从输出单元提供的时间序列模式和外部教学的动作单元所作出的动作获得的时间序列模式，用于调整从输出单元相应地提供的时间序列模式 对于输入时间序列模式，学习单元学习从输出单元提供并由调整单元调整的时间序列模式。
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9.发明授权公开(公告)号：US08122002B2
公开(公告)日：2012-02-21
申请号：US12335127
申请日：2008-12-15
申请人： Masato Ito , Kenichi Hidai , Katsuki Minamino , Kuniaki Noda
发明人： Masato Ito , Kenichi Hidai , Katsuki Minamino , Kuniaki Noda
IPC分类号： G06F17/30
CPC分类号： G06F17/30864
摘要： An information processing device includes an obtaining unit to obtain two pieces of information that are targets for searching for connections; a connection searching unit to use an action model wherein the manner of obtaining, from input information, obtain related information that relates to the input information is modeled, and find connection information to connect the two pieces of information, thereby searching connections between the two pieces of information; and a search result output unit to output the search results of the connections between the two pieces of information.
摘要翻译： 信息处理装置包括获取单元，用于获得作为搜索连接的目标的两条信息; 连接搜索单元，用于使用动作模型，其中从输入信息获得与获取与输入信息相关的相关信息的方式被建模，并且找到连接信息以连接两条信息，从而搜索两个部分之间的连接 的信息; 以及搜索结果输出单元，输出两条信息之间的连接的搜索结果。
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10.发明授权公开(公告)号：US09232205B2
公开(公告)日：2016-01-05
申请号：US13814181
申请日：2011-08-02
申请人： Hirotaka Suzuki , Masato Ito
发明人： Hirotaka Suzuki , Masato Ito
CPC分类号： H04N9/87 , G06F17/30796 , G06F17/30843 , G06F17/30852 , G06K9/00718 , G06K2209/27
摘要： An information processing device, method and a program adds an annotation to content and provides an application which utilizes the annotation. A learning module extracts an image feature amount of each frame of an image of learning content and extracts word frequency information regarding a frequency of appearance of each word in a description text, and learns an annotation models which is a multi-stream Hidden Markov Model (HMM) by using a multi-stream including the image feature amount and the text feature amount. A browsing controller extracts a scene which is a group of one or more temporally continuous frames from target content by using the annotation model and displays representative images of the scenes so as to be arranged in chronological order.
摘要翻译： 信息处理设备，方法和程序向内容添加注释并提供利用注释的应用。 学习模块提取学习内容的图像的每帧的图像特征量，并提取关于描述文本中的每个单词的出现频率的单词频率信息，并且学习作为多流隐马尔可夫模型的注释模型（ HMM）通过使用包括图像特征量和文本特征量的多流。 浏览控制器通过使用注释模型从目标内容中提取作为一个或多个时间上连续的帧的组的场景，并且以时间顺序排列场景的代表性图像。
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