CHARGE DOMAIN SYNAPSE CELL
    22.
    发明公开
    CHARGE DOMAIN SYNAPSE CELL 失效
    电荷畴突触细胞。

    公开(公告)号:EP0606213A1

    公开(公告)日:1994-07-20

    申请号:EP92912786.0

    申请日:1992-05-22

    申请人: INTEL CORPORATION

    IPC分类号: G06F15 G06G7 G06N3 H03K17

    CPC分类号: G06N3/0635 G06N3/063

    摘要: Une cellule synaptique semi-conductrice, à domaine de charge (10), comprend un condensateur (15) couplé entre une ligne d'entrée (11) et un noeud intermédiaire (17). Une transition descendante de tension, appliquée à la ligne d'entrée (11), produit un transfert de charge d'une ligne de sommation (S1) vers le noeud intermédiaire (17) par l'intermédiaire d'un premier dispositif (14) présentant un seuil programmable. Un second dispositif (13) transfère la charge du noeud intermédiaire (17) vers une autre ligne de sommation (S2) en réponse à la prochaine transition descendante de tension de la ligne d'entrée. La quantité de charge transférée est proportionnelle à l'amplitude du signal d'entrée pulsé, au seuil de tension programmé et à la valeur de capacitance.

    Adaptive-learning type product-sum operation circuit element and circuit using such element
    23.
    发明公开
    Adaptive-learning type product-sum operation circuit element and circuit using such element 失效
    Adaptiver lernender Multiplikations-Additionsschaltungsbaustein und Schaltung mit einem solchen Baustein。

    公开(公告)号:EP0584844A2

    公开(公告)日:1994-03-02

    申请号:EP93200856.8

    申请日:1993-03-25

    发明人: Ishihara, Hiroshi

    IPC分类号: G06F15/80 G06G7/60

    CPC分类号: G06N3/0635 G06N3/063

    摘要: The present invention relates to a product-sum operation circuit element and a circuit for addition by weighting a number of signals input in one neuron circuit (N₁, N₂, ... N n ) in a neural network, and can provide an adaptive-learning neuron circuit (N₁, N₂, ... N n ) for changing an interval of output pulses by learning by connecting a simple pulse generating circuit consisting of at least capacitance, resistance, unijunction transistor UJT and MISFET.
    A product-sum operation circuit element according to the present invention, comprises an insulator substrate (35), a single crystal semiconductor thin film (36, 37) having a p-n-p or n-p-n structure in a lateral direction formed in the shape of stripes on the insulator substrate (35), a ferroelectric thin film (38) deposited thereon for covering at least the semiconductor stripe structure (36, 37), and a stripe-like gate electrode 39 consisting of a metal or a polycrystalline semiconductor formed thereon for intersecting said semiconductor stripes at a right angle or suitable angle.

    摘要翻译: 本发明涉及乘积和运算电路元件和电路,用于通过对在神经网络中的一个神经元电路(N1,N2,...,Nn)中输入的多个信号进行加权来加法,并且可以提供自适应 - 通过连接由至少由电容,电阻,单结晶体管UJT和MISFET组成的简单脉冲发生电路来学习来改变输出脉冲的间隔的学习神经元电路(N1,N2,... Nn)。 根据本发明的乘积和运算电路元件包括绝缘体基板(35),在其上形成有条状的pnp或npn结构的单晶半导体薄膜(36,37) 绝缘体基板(35),沉积在其上的至少覆盖半导体条纹结构(36,37)的铁电薄膜(38)和形成在其上的由金属或多晶半导体构成的条状栅电极39,用于与所述 半导体条纹成直角或合适的角度。

    Procédé de connexion interne pour réseaux de neurones
    24.
    发明公开
    Procédé de connexion interne pour réseaux de neurones 失效
    Internes Verbindungsverfahrenfürneuronale Netzwerke。

    公开(公告)号:EP0533540A1

    公开(公告)日:1993-03-24

    申请号:EP92402490.4

    申请日:1992-09-11

    申请人: THOMSON-CSF

    发明人: Burel, Gilles

    IPC分类号: G06G7/60

    CPC分类号: G06N3/0635

    摘要: Procédé de connexion interne pour réseaux de neurones reliant des couches de neurones successives. Les états de sortie des neurones d'une nouvelle couche sont représentés par des fonctions obtenues suivant une première étape (21) en effectuant une sommation pondérée de fonctions représentant chacune l'état de sortie d'un neurone de la couche précédente, suivant une deuxième étape (22) en appliquant une fonction saturante au résultat de la sommation et suivant une troisième étape (23) en appliquant une fonction de distribution au résultat de la fonction saturante.
    Application : traitement et analyse d'image, traitement du signal.

    摘要翻译: 连接神经网络的神经网络的内部连接方法。 根据第一步骤(21),通过执​​行功能的加权求和来表示新层的神经元的输出状态,每个功能表示前一层的神经元的输出状态,根据第二步骤 (22)通过对所述求和的结果应用饱和函数,并且根据第三步骤(23),通过对饱和函数的结果应用分布函数。 应用:图像处理和分析,信号处理。

    Analog neural network for sensor image fusion
    25.
    发明公开
    Analog neural network for sensor image fusion 失效
    类似物神经元NetzwerkfürFühlerbildschmelzen。

    公开(公告)号:EP0517097A2

    公开(公告)日:1992-12-09

    申请号:EP92108987.6

    申请日:1992-05-27

    发明人: Mathur, Bimal P.

    IPC分类号: G06G7/60

    摘要: An electronic image processing system uses data provided by one or more sensors to perform cooperative computations and improve image recognition performance. A smoothing resistive network, which may comprise an integrated circuit chip, has switching elements connected to each node. The system uses a first sensory output comprising primitives, such as discontinuities or object boundaries, detected by at least a first sensor to define a region for smoothing of a second sensory output comprising at least a second, distinct output of the first sensor or a distinct output of at least a second sensor. A bit pattern for controlling the switches is generated from the detected image discontinuities in the first sensory output. The second sensory output is applied to the resistive network for data smoothing. The switches turned off by the data from the first sensory output define regional boundaries for smoothing of the data provided by the second sensory output. Smoothing operations based on this sensor fusion can proceed without spreading object characteristics beyond the object boundaries.

    摘要翻译: 电子图像处理系统使用由一个或多个传感器提供的数据来执行协同计算并提高图像识别性能。 可以包括集成电路芯片的平滑电阻网络具有连接到每个节点的开关元件。 系统使用第一感觉输出,其包括由至少第一传感器检测到的诸如不连续性或物体边界的原始图案,以定义用于平滑第二感测输出的区域,其包括第一传感器的至少第二不同输出或不同的 输出至少第二传感器。 从检测到的第一感觉输出中的图像不连续性产生用于控制开关的位模式。 第二感觉输出被应用于电阻网络进行数据平滑。 通过来自第一感觉输出的数据关闭的开关定义用于平滑由第二感觉输出提供的数据的区域边界。 基于该传感器融合的平滑操作可以在不扩展物体边界以外的物体特性的情况下进行。

    SEMICONDUCTOR DEVICE
    26.
    发明公开
    SEMICONDUCTOR DEVICE 失效
    HALBLEITERANORDNUNG。

    公开(公告)号:EP0516847A1

    公开(公告)日:1992-12-09

    申请号:EP90908684.5

    申请日:1990-06-01

    申请人: SHIBATA, Tadashi

    IPC分类号: H01L29/788

    摘要: A semiconductor device comprising on a substrate a first semiconductor region of one conductive type, first source and and drain regions of the opposite conductive type formed in the above regions, a first gate electrode formed in a region separating said source and drain regions, the first gate electrode being electrically floated through an insulating film, and at least two second gate electrodes connected to said gate electrode by capacitive coupling, wherein an inverted layer is formed under said first gate electrode and said first source and drain regions are electrically connected together only when a predetermined threshold value is exceeded by an absolute value of a value obtained by linearly summing up the weighed voltages applied to the second gate electrodes.

    摘要翻译: 一种半导体器件,在衬底上包括一个导电类型的第一半导体区域,形成在上述区域中的相反导电类型的第一源极和漏极区域,形成在分离所述源极和漏极区域的区域中的第一栅电极, 栅电极通过绝缘膜电浮动;以及至少两个第二栅电极,通过电容耦合连接到所述栅电极,其中在所述第一栅电极下方形成反向层,并且所述第一源极和漏极区仅当 通过对施加到第二栅电极的加权电压进行线性相加而获得的值的绝对值超过预定阈值。

    Manufacturing adjustment during article fabrication
    27.
    发明公开
    Manufacturing adjustment during article fabrication 失效
    FertigungsjustierungwährendProduktherstellung。

    公开(公告)号:EP0443249A2

    公开(公告)日:1991-08-28

    申请号:EP90313203.3

    申请日:1990-12-05

    申请人: AT&T Corp.

    IPC分类号: G06F15/80 H01J37/302

    摘要: The use of neural networks has been employed to adjust processing during the fabrication of articles. For example, in the production of photolithographic masks by electron beam irradiation of a mask blank in a desired pattern, electrons scattered from the mask substrate cause distortion of the pattern. Adjustment for such scattering is possible during the manufacturing process by employing an adjustment function determined by a neural network whose parameters are established relative to a prototypical mask pattern.

    摘要翻译: 已经使用神经网络来调整制品制造过程中的处理。 例如,在通过掩模坯料的电子束照射以期望的图案制造光刻掩模时,从掩模基板散射的电子导致图案的变形。 通过采用由相对于原型掩模图案建立参数的神经网络确定的调整函数,在制造过程中可以进行这种散射的调整。

    Inductively coupled neural network
    28.
    发明公开
    Inductively coupled neural network 失效
    神经元Netzwerk mit induktiver Kopplung。

    公开(公告)号:EP0443208A2

    公开(公告)日:1991-08-28

    申请号:EP90125850.9

    申请日:1990-12-31

    IPC分类号: G06F15/80 G06F7/50

    CPC分类号: G06N3/0635 G06N3/063

    摘要: A neural coupling is composed of a pair of primary and secondary members (13,14) for coupling a precedent node (10) to a subsequent node (11) to synaptically transmit a signal through a neural network. A primary member is receptive of a signal from a precedent node for generating an inductive field according to the received signal. A secondary member is spatially coupled to the primary member through the inductive field for producing to a subsequent node a corresponding signal in response to the inductive field so as to effect synaptic transmission of the signal through the neural network.

    摘要翻译: 神经耦合由一对主要和次要成员(13,14)组成,用于将先前节点(10)耦合到后续节点(11)以通过神经网络来突触传送信号。 主要成员接受来自先验节点的信号,用于根据接收到的信号产生感应场。 辅助构件通过感应场与主构件空间耦合,以响应于感应场向后续节点产生相应的信号,以便通过神经网络进行信号的突触传输。

    Neural network having an associative memory that learns by example
    29.
    发明公开
    Neural network having an associative memory that learns by example 失效
    具有通过实例学习的相关记忆的神经网络

    公开(公告)号:EP0377908A3

    公开(公告)日:1991-03-20

    申请号:EP89124173.9

    申请日:1989-12-30

    IPC分类号: G06G7/60 G11C15/04 G06F15/80

    摘要: A neural network utilizing the threshold characteristics of a semiconductor device as the various memory elements of the network. Each memory element comprises a complementary pair of MOSFETs in which the threshold voltage is adjusted as a function of the input voltage to the element. The network is able to learn by example using a local learning algorithm. The network includes a series of output amplifiers in which the output is provided by the sum of the outputs of a series of learning elements coupled to the amplifier. The output of each learning element is the difference between the input signal to each learning element and an individual learning threshold at each input. The learning is accomplished by charge trapping in the insulator of each individual input MOSFET pair. The thresholds of each transistor automatically adjust to both the input and output voltages to learn the desired state. After input patterns have been learned by the network, the learning function is set to zero so that the thresholds remain constant and the network will come to an equilibrium state under the influence of a test input pattern thereby providing, as an output, the learned pattern most closely resembling the test input pattern.

    Neural network with dynamic refresh capability
    30.
    发明公开
    Neural network with dynamic refresh capability 失效
    Neurales Netz mit dynamischer“刷新”-Möglichkeit。

    公开(公告)号:EP0322071A2

    公开(公告)日:1989-06-28

    申请号:EP88202959.8

    申请日:1988-12-19

    IPC分类号: G06F15/06

    CPC分类号: G06N3/063 G06N3/0635

    摘要: An analog neural network composed of an array of capacitors (C1j, C2j...Cnj) for storing weighted electric charges. Electric charges, or voltages, on the capacitors control the impedance (resistance) values of a corresponding plurality of MOSFETs (28, 29...30) which selectively couple input signals to one input of a summing amplifier (31). A plurality of semiconductor gating elements (e.g. MOSFETs) (25, 26..27) selectively couple to the capacitor's weighted analog voltage values received sequentially over an input line (18). The weighted voltages on the input line are periodically applied to the proper capacitors in the neural network via the gating elements so as to refresh the weighted electric charges on the capacitors, and at a multiplex rate that maintains the voltages on the capacitors within acceptable tolerance levels.

    摘要翻译: 由用于存储加权电荷的电容器组(C1j,C2j ... Cnj)组成的模拟神经网络。 电容器上的电荷或电压控制将输入信号选择性地耦合到加法放大器(31)的一个输入端的相应多个MOSFET(28,29 ... 30)的阻抗(电阻)值。 多个半导体门控元件(例如MOSFET)(25,26..27)选择性地耦合到在输入线(18)上顺序接收的电容器加权的模拟电压值。 通过门控元件将输入线上的加权电压周期性地施加到神经网络中的适当的电容器,以便刷新电容器上的加权电荷,并且以使电容器上的电压保持在可接受的公差电平内的多路复用速率 。