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fractal-use
分形的练习一
①Koch曲线
用复数的方法来迭代Koch曲线
clear i 防止i被重新赋值
A=[0 1] 初始A是连接（0，0）与（1，0）的线段
t=exp(i*pi/3)
n=2 n是迭代次数
for j=0:n
A=A/3 a=ones(1,2*4^j)
A=[A (t*A+a/3) (A/t+(1/2+sqrt(3)/6*i)*a) A+2/3*a]
end
plot(real(A),imag(A))
axis([0 1 -0.1 0.8])
②Sierpinski三角形
A=[0 1 0.5 0 0 1] 初始化A
n=3 迭代次数
for i=1:n
A=A/2 b=zeros(1,3^i) c=ones(1,3^i)/2
A=[A A+[c b] A+[c/2 c]]
end
for i=1:3^n
patch(A(1,3*i-2:3*i),A(2,3*i-2:3*i), b ) patch填充函数
end
(Fractal
Exercise One
The ① Koch curve
Plural iteration Koch curve
clear i to prevent i is reassigned
A = [0 1] initial A is a connection (0,0) and (1,0) of the segments
t = exp (i* pi/3)
n = 2 n is the number of iterations
for j = 0: n
A = A/3 a = ones (1,2* 4 ^ j)
A = [A (t* A+ a/3) (A/t+ (1/2+ sqrt (3)/6* i)* a) A+2/3* a]
end
plot (real (A), imag (A))
axis ([0 1-0.1 0.8])
② Sierpinski triangle
A = [0 1 0.5 0 0 1] initialized A
n = 3 the number of iterations.
for i = 1: n
A = A/2 b = zeros (1,3 ^ i) c = ones (1,3 ^ i)/2
A = [A A+ [c b] A+ [c/2 c]]
end
for i = 1:3 ^ n
patch (A (1,3* i-2: 3* i), A (2,3* i-2: 3* i), b ) patch filled function
end)
- 2013-03-02 10:03:09下载
- 积分：1
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- 积分：1
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CIMET
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3.20 基于Hough变换的人眼虹膜定位方法
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gaosi
说明： 对原始图像添加高斯噪声，并用邻域平均和中值滤波法进行滤波，并可以进行对比。(Gaussian noise added to the original image, and use neighborhood average and median filtering method for filtering, and can be compared.)
- 2011-02-21 13:18:13下载
- 积分：1
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- 2014-09-29 14:22:16下载
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