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    • 5. 发明授权
    • Information retrieval system
    • 信息检索系统
    • US5504884A
    • 1996-04-02
    • US14253
    • 1993-02-05
    • Kazuo KyumaShuichi TaiMasaya OitaNagaaki OhyamaMasahiro Yamaguchi
    • Kazuo KyumaShuichi TaiMasaya OitaNagaaki OhyamaMasahiro Yamaguchi
    • G06F15/18G06F17/30G06N99/00G06F15/17
    • G06F17/30997Y10S707/99935
    • An information retrieval system allowing the user to build a database or to retrieve data therefrom based on vague retrieval-designating data without becoming aware of the database structure. The system comprises a neural network, a memory, an interface part and a CRT. The neural network stores data designating electronic still pictures contained in the memory. When data for designating retrieval are input, the interface part groups the data into such categories as the place where the desired picture was taken and the date on which it was taken, and supplies the neural network with the categorized input data. In turn, the neural network outputs by association the data corresponding to the input data. Given the data from the network, the memory outputs the relevant electronic still picture to the CRT for display.
    • 一种信息检索系统,其允许用户构建数据库或者基于模糊的检索指定数据来检索数据,而不会意识到数据库结构。 该系统包括神经网络,存储器,接口部分和CRT。 神经网络存储指定存储器中包含的电子静态图片的数据。 当输入用于指定检索的数据时,接口部分将数据分组成所需图像的位置和拍摄日期的类别,并将神经网络提供分类的输入数据。 反过来,神经网络通过关联与输入数据相对应的数据来输出。 给定来自网络的数据,存储器将相关的电子静态图像输出到CRT以进行显示。
    • 6. 发明授权
    • Knowledge information processing system including two associative memory
groups each including a plurality of associated memory units
    • 知识信息处理系统包括两个关联存储器组,每个存储器组包括多个关联的存储器单元
    • US5418886A
    • 1995-05-23
    • US624
    • 1993-01-05
    • Masaya OitaShuichi TaiKazuo Kyuma
    • Masaya OitaShuichi TaiKazuo Kyuma
    • G06F15/18G06F9/44G06G7/60G06N3/04G06N3/08G06N99/00
    • G06F9/4438
    • The knowledge information processing system includes a first and second associative memory unit groups. The associative memory units of the first associative memory unit group 1 associates a plurality of distinct features to the input pattern 20. In response to the combination of associated outputs from the first associative memory unit group 1, the second associative memory unit group 4 evaluates and associates features corresponding to those associated by the first associative memory unit group 1. The logical operation unit group 6 compares the associated outputs of the first associative memory unit group 1 with those of the second to judge whether or not corresponding associated outputs agree with each other. If the corresponding associated outputs do not agree, the logical operation unit group 6 outputs feedback information items for correcting the energy functions of the first associative memory unit group 1, thereby repeating the association and the evaluation process.
    • 知识信息处理系统包括第一和第二关联存储器单元组。 第一关联存储器单元组1的相关存储器单元将多个不同特征与输入模式20相关联。响应于来自第一关联存储器单元组1的相关联的输出的组合,第二关联存储器单元组4评估 将与第一关联存储器单元组1相关联的特征相关联。逻辑运算单元组6将第一关联存储器单元组1的相关联的输出与第二关联存储单元组1的相关联的输出进行比较,以判断对应的相关输出是否彼此一致 。 如果对应的相关输出不一致,则逻辑运算单元组6输出用于校正第一关联存储单元组1的能量函数的反馈信息项,从而重复该关联和评估处理。
    • 10. 发明授权
    • Optical neural network
    • 光学神经网络
    • US5095459A
    • 1992-03-10
    • US375813
    • 1989-07-05
    • Jun OhtaKazuo KyumaShuichi TaiMasaya Oita
    • Jun OhtaKazuo KyumaShuichi TaiMasaya Oita
    • G06K9/74G06N3/067
    • G06K9/74G06N3/067
    • An optical neural network which imitates a biological neural network, to provide an associative and/or pattern recognition function, is made of light emitting elements to represent an input neuron state vector, a correlation matrix which modulates light according to stored vector information, light receiving elements, an accumulator and a comparator to perform a threshold function. A stored vector closest to an input vector can be found from a large amount of information without increasing the system size by dividing the correlation matrix and the input neuron state vector with time division techniques, frequency modulation or phase modulation techniques. Positive and negative valves can also be provided with similar techniques.
    • 模拟生物神经网络以提供关联和/或模式识别功能的光学神经网络由发光元件构成,以表示输入神经元状态向量,根据存储的矢量信息调制光的相关矩阵,光接收 元素,累加器和比较器来执行阈值函数。 可以从大量信息找到最接近输入向量的存储向量,而不需要通过用相关矩阵和输入神经元状态向量与时分技术,频率调制或相位调制技术相除来增加系统大小。 正极和负极阀也可以提供类似的技术。