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双输入单输出系统
x1(1)=1 x2(1)=1 d(1)=1
x1(2)=-0.5 x2(1)=-1 d(1)=-1
x1(3)=3 x2(1)=1 d(1)=1
x1(4)=-2 x2(1)=-1 d(1)=-1
建立一个感知器网络,实现上述样本的分类,计算出相应的网络权值矩阵W-Dual-input single-output system x1 (1) = 1 x2 (1) = 1 d (1) = 1 x1 (2) =-0.5 x2 (1) =-1 d (1) =-1 x1 (3) = 3 x2 (1) = 1 d (1) = X1 (4) =-2 X2 (1) =-1 D (1) =-1 establish a perceptron network, and to achieve the classification of the above samples, calculate the corresponding network weight matrix W
x1(1)=1 x2(1)=1 d(1)=1
x1(2)=-0.5 x2(1)=-1 d(1)=-1
x1(3)=3 x2(1)=1 d(1)=1
x1(4)=-2 x2(1)=-1 d(1)=-1
建立一个感知器网络,实现上述样本的分类,计算出相应的网络权值矩阵W-Dual-input single-output system x1 (1) = 1 x2 (1) = 1 d (1) = 1 x1 (2) =-0.5 x2 (1) =-1 d (1) =-1 x1 (3) = 3 x2 (1) = 1 d (1) = X1 (4) =-2 X2 (1) =-1 D (1) =-1 establish a perceptron network, and to achieve the classification of the above samples, calculate the corresponding network weight matrix W
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