59300

说明：  拉普拉斯分解(Laplacian decomposition)

计算轨道角动量的纯度,解调的纯度分布情况存到一个用户自定义的TXT文档中(Calculate the purity of orbital angular momentum )

基于matlab平台有理分式多项式法模态参数识别(Based on matlab platform rational fraction polynomial method modal parameter identification)

采用Monta Carlo 方法求Pi值方法，并画出圆内随机点(Monta Carlo method, to calculate the value of Pi method, and draw a random point within the circle)

PLOT RECEIVING END VOLTAGE (Vr/Vs) AS A FUNCTION OF (P/Po) FOR UNCOMPENSATED AS WELL AS L-C COMPENSATED LINES AT LOAD AT PARTICULAR LENGTH OF LINE. TAKE Ø = 0, 0.866 LAG & 0.866 LEAD AND LEGTH OF TRANSMISSION LINE 200 KM, 400 KM & 500 KM. EXPLAIN THE VOLTAGE VARIATION OF LINE.

梯度下降法是最早最简单，也是最为常用的最优化方法。梯度下降法实现简单，当目标函数是凸函数时，梯度下降法的解是全局解。一般情况下，其解不保证是全局最优解，梯度下降法的速度也未必是最快的。梯度下降法的优化思想是用当前位置负梯度方向作为搜索方向，因为该方向为当前位置的最快下降方向，所以也被称为是”最速下降法“。最速下降法越接近目标值，步长越小，前进越慢。(The gradient descent method is the earliest and most simple and most commonly used optimization method. The gradient descent method is simple to realize. When the objective function is a convex function, the solution of the gradient descent method is a global solution. In general, the solution is not guaranteed to be the global optimal solution, and the gradient descent method is not necessarily the fastest. The optimization idea of gradient descent method is to use the current position negative gradient direction as the search direction, because the direction is the fastest descending direction of the current position, so it is also called the steepest descent method. The faster the slowest descent approach is closer to the target, the smaller the step, the slower the progress.)

模式识别课小作业，利用贝叶斯最小错误率预测，实现细胞正常不不正常的区分(Pattern recognition homework)

无限状态隐马尔可夫模型(IHMM)采样与推理算法程序,可用于模式识别,视频异常事件检测等,开发平台了最新的MATLAB2009(Infinite state Hidden Markov Model (IHMM) sampling procedures and the reasoning algorithm can be used for pattern recognition, video detection of abnormal events such as the development platform, the latest MATLAB2009)

获取导航电文，通过卷积地方法，十分有用，希望能够帮助大家！(Access to the navigation message, through the method of convolution and is very useful to help you!)

boost 非线性分叉仿真 完整出图 效果明显(boost non-linear simulation complete bifurcation diagram showing the effect of significantly)