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Hopfield

于 2014-05-02 发布文件大小:8KB

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离散Hopfield神经网络的数字识别，可作为学习参考(Digital identification of discrete Hopfield neural networks can be used as a reference to learn)

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说明：本程序可以绘制p3曲线，直接输入cv、cs、EX,也通过降雨或径流数据计算绘制 [cs,cv,ma] = p3plot(a,kk,b,bb,y1,cs_cv,ma,cs,cv,x0) a=20 横向网格条数 kk=200 纵坐标标注间隔（间隔要是最大值和最小值差的整数倍） b=2000 纵坐标最大值 bb=0 纵坐标最小值 y1=[] 降雨量，横向矩阵输入,如果没有请输入[] cs_cv=[2] 没有，请输入[] ma=[] 年平均降雨量，没有输入[] cs=[] 没有，请输入[] cv=[] 没有，请输入[] x0=0.01 初始概率点，百分数,没有输入[]( this program can draw P3 curve, direct input CV, CS, EX, also by rainfall or runoff data calculation and drawing The [cs, CV, ma] = p3plot (a, KK, B, BB, Y1, cs_cv, Ma, CS, CV, x0) The a=20 of the number of horizontal grid The kk=200 longitudinal coordinate labeling interval (interval if the maximum value and the minimum value of the integer times the difference) The b=2000 of the maximum longitudinal coordinates The bb=0 of the minimum longitudinal coordinates The y1=[] rainfall, transverse matrix input, if not please input [] The cs_cv=[2] no, please enter [] The ma=[] of the average annual rainfall no input []. The cs=[] no, please enter [] The cv=[] no, please enter [] x0=0.01 initial probability, percentage, no input [])

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Hopfield

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