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    • 41. 发明授权
    • Phase-locked loop oscillatory neurocomputer
    • 锁相环振荡神经计算机
    • US07280989B1
    • 2007-10-09
    • US09771019
    • 2001-01-26
    • Frank C. HoppensteadtEugene M. Izhikevich
    • Frank C. HoppensteadtEugene M. Izhikevich
    • G06E1/00G06E3/00G06F15/18G06G7/00G06N3/00
    • G06N3/049G06K9/46
    • A neural network computer (20) includes a weighting network (21) coupled to a plurality of phase-locked loop circuits (251-25N). The weighting network (21) has a plurality of weighting circuits (C11, . . . , CNN) having output terminals connected to a plurality of adder circuits (311-31N). A single weighting element (Ckj) typically has a plurality of output terminals coupled to a corresponding adder circuit (31k). Each adder circuit (31k) is coupled to a corresponding bandpass filter circuit (31k) which is in turn coupled to a corresponding phase-locked loop circuit (25k). The weighting elements (C1,1, . . . , CN,N) are programmed with connection strengths, wherein the connection strengths have phase-encoded weights. The phase relationships are used to recognize an incoming pattern.
    • 神经网络计算机(20)包括耦合到多个锁相环电路(25-125N)的加权网络(21)。 加权网络(21)具有多个具有连接到多个加法器电路(31')的输出端的加权电路(C 11,...,C N N N) SUB> 1< N< N< N>)。 单个加权元件(C j j>))。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。 每个加法器电路(31KK)耦合到对应的带通滤波器电路(31K),该相应的带通滤波器电路又耦合到相应的锁相环电路(25 k )。 加权元件(C 1,1,...,C N,N N)用连接强度编程,其中连接强度具有相位编码权重。 相位关系用于识别输入模式。