| 1. | Simple algorithm for probability density of function in two random variable
关于二维随机变量函数的概率密度的一种简便算法 |
| 2. | Calculating skill on the distribution of2 - dimensional continuous random variable functions
二维连续型随机变量函数的分布计算技巧 |
| 3. | The distribution for function of variables is an important but difficult to be mastered course
摘要随机变量函数的分布是数学系概率统计课程教学中的一个重点和难点。 |
| 4. | It is found that the high order frequency response functions of these systems will become single frequency variable functions
对于这些系统它们的高阶频率响应函数将成为单一的频率变量函数。 |
| 5. | Though studying some formulas in theory of probability , we give the formula conditional probability in complete event set and a simplified formula for density ' s function in two random variables , they offer new methods in calculation
摘要通过对概率论中有关公式的研究，给出了全条件概率公式和二维随机变量函数的密度函数的简化计算公式，为其计算提供了新的方法。 |
| 6. | The main idea of this method include two steps : at first , the approximate expression of function is obtained by method of weighted residuals ; then the first and second moment of the random function can be calculated with method of moment
该方法的基本思想是利用加权残值法获得问题解的近似函数表达式，在此基础上利用求解随机变量函数的矩法求得随机函数的一、二阶矩等统计数字特征。 |
| 7. | A necessary and sufficient condition with ergodic of 1 - order probability distribution function of stochastic process ( theorem 1 and corollary 1 ) and extended the general distribution theorem of stochastic variable under the case of weakly condition ( theorem2 ) are presented
摘要提出了随机过程一阶概率分布函数具有遍历性的一个充分必要条件（定理1和推论1 ） ，并在较弱条件下，对一般的关于随机变量函数分布定理作了进一步的推广（定理2 ） 。 |
| 8. | Based on the analysis of the methods for optimizing the fuzzy neural networks before , this paper has finished following works : 1 ) we proposed a learning algorithm based on tabu search for fuzzy neural networks based on the model of anfis proposed by jyh - shing roger jang . then used the system for one variable function ' s approximation . 2 ) based on the first research , we improved the tabu search algorithm for the purpose of approximating complex functions . 3 ) analysis the capabilities of tabu search , and discuss the approximation ability and generalization ability of the fuzzy neural networks system according to the compute results
本文在对以前的模糊神经网络参数学习算法进行分析的基础上，做了以下几个方面的工作： 1 )根据禁忌搜索算法的特点，在jyh - shingrogerjang提出的anfis模型的基础上，将禁忌搜索算法应用于模糊神经网络线性和非线性参数的学习上，并将该模型用于单变量函数的逼近； 2 )在第一阶段的基础上，对算法进行了改进，使改进后的算法能够适用于复杂的ii函数逼近问题; 3 )根据计算机仿真的结果，对禁忌搜索算法的性能进行了分析，并对该模糊神经系统的函数逼近能力和泛化能力进行了讨论。 |
| 9. | The obtained results in the paper are as follows : ( 1 ) the expansion of fourier series of orthogonal trigonometric polynomial for conditional mathematical expectation and function of random variable ; ( 2 ) the best approximation of trigonometric polynomial about another random variable for function of a random variable ; ( 3 ) the best approximation order of trigonometric polynomial for function of random variable
摘要获得了如下结果： ( 1 )条件数学期望及随机变量函数的三角多项式级数表达； ( 2 )一个随机变量关于另一个随机变量的三角多项式的最佳逼近； ( 3 )随机变量函数被随机变量三角多项式最佳逼近的阶。 |
