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Check the inverse relationship between the shift distance and the number of iterations

2022-08-06 07:06:00 【black elm】

(A,B)---m*n*k---(1,0)(0,1)

移位距离和假设

用神经网络分类A和B,把参与分类的A和B中的数字看作是组成A和B的粒子,分类的过程就是让A和B中的粒子互相交换位置,寻找最短移位路径的过程.而熵HWith the shift of shortest distance andS成正比,迭代次数n与熵H成反比.

移位规则汇总

每个粒子移位一次,位置重合不移位,A single shift distance if the image in order to1为底等于1-元素数值若以0为底则为元素本身.

分类8116,A中只有一个0.8,B中有3个不为0的值.The number of iterations to estimate this group of pictures.

按照移位距离和假设,This group of pictures shift distance of4-0.8-0.1-0.1-0.6=2.4

8123The shift distance as2.6,The number of iterations the last experiment has been

8123

δ

迭代次数n

5.00E-04

28525.63

4.00E-04

34343.1

3.00E-04

44964.48

2.00E-04

65561.12

1.00E-04

124472.5

s

2.6

According to the shift distance and inverse relationship with the number of iterations2.4<2.6,Is the relationship between the number of iterations should be8116>8123

8116Number of iterations of the measured values for

8116

δ

迭代次数n

5.00E-04

28917.729

4.00E-04

35497.623

3.00E-04

46176.704

2.00E-04

67179.523

1.00E-04

126701.39

s

2.4

Analyzing the relationship between

8116

8123

8116-8123

δ

迭代次数n

迭代次数n

5.00E-04

28917.729

28525.63

392.09864

4.00E-04

35497.623

34343.1

1154.5231

3.00E-04

46176.704

44964.48

1212.2235

2.00E-04

67179.523

65561.12

1618.4026

1.00E-04

126701.39

124472.5

2228.892

s

2.4

2.6

8116>8123,The results conform to the assumption.

771

122

δ

迭代次数n

迭代次数n

5.00E-04

28114.19

25862.05

4.00E-04

34375.59

31524.1

3.00E-04

44667.95

41011.36

2.00E-04

64534.3

59270.11

1.00E-04

123420.9

112397.9

S

2

3

The experiment has beens=2和3的迭代次数,粗略估算s=2.4的迭代次数为119011,实测值为126701,二者相差6.5%,Small forecasts.

According to the hypothesis as long ass=2.4The number of iterations should be all the same,继续实验

分类8116,8125,8134,8224,8233,这5组的s都等于2.4.The number of iterations for

8134

8116

8125

8224

8233

δ

迭代次数n

迭代次数n

迭代次数n

迭代次数n

迭代次数n

5.00E-04

29615.58

28917.73

29552.14

29905.67

30245.28

4.00E-04

36047.14

35497.62

36133.77

36531.3

36726.87

3.00E-04

46776.77

46176.7

46885.2

46887.09

47950.08

2.00E-04

68050.53

67179.52

67496.68

68083.92

68372.68

1.00E-04

128497.9

126701.4

129570.6

130194.2

129414.1

s

2.4

2.4

2.4

2.4

2.4

Shift distance and assumptions to estimate the image binarization of iterations will bring the error,But this group of data is very close to each other,Only between the maximum and the minimum2.7%,This conforms to the assumption.用130194去和119011More than forecast9.4%

Compared with the experimental data

981

871

971

881

861

771

122

961

875

δ

迭代次数n

迭代次数n

迭代次数n

迭代次数n

迭代次数n

迭代次数n

迭代次数n

迭代次数n

迭代次数n

5.00E-04

34219.01

34553.02

28229.22

27843.89

28270.21

28114.19

25862.05

25523.99

25117.39

4.00E-04

41899.68

41568.85

34548.15

34511.79

34803.25

34375.59

31524.1

30958.15

31102.23

3.00E-04

53474.56

54287.27

44497.27

44407.41

45065.05

44667.95

41011.36

40262.78

40239.05

2.00E-04

77797.83

78173.77

64693.36

64832.42

64707.93

64534.3

59270.11

59096.97

58618.7

1.00E-04

148175

146473.4

123601.3

122874.1

123288

123420.9

112397.9

113446.1

111994.6

s

1

1

2

2

2

2

3

3

3

851

951

866

777

941

854

931

921

911

δ

迭代次数n

迭代次数n

迭代次数n

迭代次数n

迭代次数n

迭代次数n

迭代次数n

迭代次数n

迭代次数n

5.00E-04

25288.76

23904.73

23868.01

23579.5

22959.57

22738.92

22166.65

22094.36

23575.86

4.00E-04

31347.55

28978.03

28820.87

28965.92

27774.2

27653.1

27290.48

27253.6

28991.81

3.00E-04

40549.93

38252.24

37659.14

37460.82

35993.35

36072.61

35639.73

35340.25

37399.98

2.00E-04

59255.58

55426.48

54661.18

54804.67

52950.71

53116.99

51890.25

52155.43

54335.16

1.00E-04

114094.8

106880.8

106599.8

106112.6

101146.2

100986.2

100158

98502.28

102787.2

s

3

4

4

4

5

5

6

7

8

8116

8123

δ

迭代次数n

迭代次数n

5.00E-04

28917.729

28525.63

4.00E-04

35497.623

34343.1

3.00E-04

46176.704

44964.48

2.00E-04

67179.523

65561.12

1.00E-04

126701.39

124472.5

s

2.4

2.6

误差

6.5-9.4%

5.9-6.7%

原网站

版权声明
本文为[black elm]所创，转载请带上原文链接，感谢
https://yzsam.com/2022/218/202208060623097326.html

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