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    • 1. 发明授权
    • Multiple error and fault diagnosis based on Xlists
    • 基于Xlists的多重错误和故障诊断
    • US06532440B1
    • 2003-03-11
    • US09173962
    • 1998-10-16
    • Vamsi BoppanaRajarshi MukherjeeJawahar JainMasahiro Fujita
    • Vamsi BoppanaRajarshi MukherjeeJawahar JainMasahiro Fujita
    • G06F1750
    • G01R31/31835
    • A method and system for locating possible error or fault sites in a circuit or system. A set of nodes are chosen, using error models in some embodiments. By applying X values to the set of nodes in conjunction with three valued logic simulation output responses between the circuit and the specification are determined. Based on the comparison of the output responses between the circuit and the specification, an error probability can be assigned to the set of nodes. A ranked set of nodes is thereby produced with the highest ranked set of nodes being the most likely error or fault site. Furthermore, by determining the relationship of the inputs to the set of nodes to the outputs of the set of nodes in conjunction with test vectors and output responses determined in the specification, an error probability can also be assigned to the set of nodes. Use of symbolic logic variables can assist in determining the relationship of the inputs to the set of nodes to the outputs of the set of nodes.
    • 一种用于定位电路或系统中可能的错误或故障位置的方法和系统。 在一些实施例中使用误差模型来选择一组节点。 通过将X值应用于节点集合并结合电路与规范之间的三值逻辑模拟输出响应。 基于电路和规范之间的输出响应的比较,可以将错误概率分配给该组节点。 由此产生排列的节点集合,其中最高排名的节点集合是最可能的错误或故障站点。此外,通过结合测试来确定输入与节点集合到节点集合的输出的关系 在规范中确定的向量和输出响应,也可以将错误概率分配给该组节点。 使用符号逻辑变量可以帮助确定输入与节点集合到该组节点的输出的关系。
    • 2. 发明授权
    • Image processing system, learning device and method, and program
    • 图像处理系统,学习装置和方法,程序
    • US08582887B2
    • 2013-11-12
    • US11813404
    • 2005-12-26
    • Hirotaka SuzukiAkira NakamuraTakayuki YoshigaharaKohtaro SabeMasahiro Fujita
    • Hirotaka SuzukiAkira NakamuraTakayuki YoshigaharaKohtaro SabeMasahiro Fujita
    • G06K9/00
    • G06K9/00288G06K9/6211G06K9/623G06T7/00
    • The present invention relates to an image processing system, a learning device and method, and a program which enable easy extraction of feature amounts to be used in a recognition process. Feature points are extracted from a learning-use model image, feature amounts are extracted based on the feature points, and the feature amounts are registered in a learning-use model dictionary registration section 23. Similarly, feature points are extracted from a learning-use input image containing a model object contained in the learning-use model image, feature amounts are extracted based on these feature points, and these feature amounts are compared with the feature amounts registered in a learning-use model registration section 23. A feature amount that has formed a pair the greatest number of times as a result of the comparison is registered in the model dictionary registration section 12 as the feature amount to be used in the recognition process. The present invention is applicable to a robot.
    • 本发明涉及图像处理系统,学习装置和方法以及能够容易地提取在识别处理中使用的特征量的程序。 从学习用模型图像提取特征点,基于特征点提取特征量,并且将特征量登记在学习用模型字典注册部23中。同样,从学习用途中提取特征点 基于这些特征点提取含有包含在学习用模型图像中的模型对象的输入图像,并将这些特征量与在学习用模型登记部23中登记的特征量进行比较。特征量 作为比较的结果,在模型字典登记部12中登记了作为识别处理中使用的特征量的最大次数的对。 本发明可应用于机器人。
    • 9. 发明申请
    • Robot apparatus
    • 机器人装置
    • US20050187662A1
    • 2005-08-25
    • US11099139
    • 2005-04-04
    • Kotaro SabeMasahiro Fujita
    • Kotaro SabeMasahiro Fujita
    • A63F13/00A63H11/00B25J5/00B25J9/18B25J13/00B25J13/08G06N3/00G06F19/00
    • G06N3/008A63H11/00B25J11/0005
    • A robot apparatus is provided. A CPU 15 determines an output of a feeling model based on signals supplied from a touch sensor 20. The CPU 15 also deciphers whether or not an output value of the feeling model exceeds a pre-set threshold value. If the CPU finds that the output value exceeds the pre-set threshold value, it verifies whether or not there is any vacant area in a memory card 13. If the CPU finds that there is any vacant area in a memory card 13, it causes the picture data captured from the CCD video camera 11 to be stored in the vacant area in the memory card 13. At this time, the CPU 15 causes the time and date data and the feeling parameter in the memory card 13 in association with the picture data. The CPU 15 also re-arrays the picture data stored in the memory card 13 in the sequence of the decreasing magnitude of the feeling model output.
    • 提供了一种机器人装置。 CPU15基于从触摸传感器20提供的信号确定感觉模型的输出。 CPU15还解密感觉模型的输出值是否超过预先设定的阈值。 如果CPU发现输出值超过预定阈值,则验证存储卡13中是否有空的区域。 如果CPU发现存储卡13中存在任何空闲区域,则将从CCD摄像机11捕获的图像数据存储在存储卡13的空闲区域中。 此时,CPU15与图像数据相关联地导致存储卡13中的时间和日期数据和感觉参数。 CPU15还按照感觉模型输出的衰减幅度的顺序重新排列存储在存储卡13中的图像数据。