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| ===Nonnegativity 非负性=== | | ===Nonnegativity 非负性=== |
| The joint entropy of a set of random variables is a nonnegative number. | | The joint entropy of a set of random variables is a nonnegative number. |
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| 一组随机变量的联合熵是一个非负数。 | | 一组随机变量的联合熵是一个非负数。 |
− | :<math>\Eta(X,Y) \geq 0</math>
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− | :<math>\Eta(X_1,\ldots, X_n) \geq 0</math> | + | |
| + | :<math>H(X,Y) \geq 0</math> |
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| + | :<math>H(X_1,\ldots, X_n) \geq 0</math> |
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| === Greater than individual entropies 大于单个熵=== | | === Greater than individual entropies 大于单个熵=== |
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| The joint entropy of a set of variables is greater than or equal to the maximum of all of the individual entropies of the variables in the set. | | The joint entropy of a set of variables is greater than or equal to the maximum of all of the individual entropies of the variables in the set. |
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| 一组变量的联合熵大于或等于该组变量的所有单个熵的最大值。 | | 一组变量的联合熵大于或等于该组变量的所有单个熵的最大值。 |
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− | :<math>\Eta(X,Y) \geq \max \left[\Eta(X),\Eta(Y) \right]</math>
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− | :<math>\Eta \bigl(X_1,\ldots, X_n \bigr) \geq \max_{1 \le i \le n} | + | :<math>H(X,Y) \geq \max \left[H(X),H(Y) \right]</math> |
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| + | :<math>H \bigl(X_1,\ldots, X_n \bigr) \geq \max_{1 \le i \le n} |
| \Bigl\{ \Eta\bigl(X_i\bigr) \Bigr\}</math> | | \Bigl\{ \Eta\bigl(X_i\bigr) \Bigr\}</math> |
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| === Less than or equal to the sum of individual entropies 小于或等于单个熵的总和=== | | === Less than or equal to the sum of individual entropies 小于或等于单个熵的总和=== |
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| The joint entropy of a set of variables is less than or equal to the sum of the individual entropies of the variables in the set. This is an example of [[subadditivity]]. This inequality is an equality if and only if <math>X</math> and <math>Y</math> are [[statistically independent]].<ref name=cover1991 />{{rp|30}} | | The joint entropy of a set of variables is less than or equal to the sum of the individual entropies of the variables in the set. This is an example of [[subadditivity]]. This inequality is an equality if and only if <math>X</math> and <math>Y</math> are [[statistically independent]].<ref name=cover1991 />{{rp|30}} |
− | 一组变量的联合熵小于或等于该组变量各个熵的总和。这是次可加性的一个例子。即当且仅当<math>X</math>和<math>Y</math>在统计上独立时,该不等式才是等式。
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− | :<math>\Eta(X,Y) \leq \Eta(X) + \Eta(Y)</math> | + | 一组变量的联合熵小于或等于该组变量各个熵的总和。这是次可加性的一个例子。即当且仅当<math>X</math>和<math>Y</math>在统计上独立时,该不等式才是等式。<ref name=cover1991 />{{rp|30}} |
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| + | :<math>H(X,Y) \leq H(X) + H(Y)</math> |
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− | :<math>\Eta(X_1,\ldots, X_n) \leq \Eta(X_1) + \ldots + \Eta(X_n)</math> | + | :<math>H(X_1,\ldots, X_n) \leq H(X_1) + \ldots + H(X_n)</math> |
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| ==Relations to other entropy measures== | | ==Relations to other entropy measures== |