2nd

IGBT的boost电路，最简单的，适合初学者(IGBT in the boost circuit, the most simple, suitable for beginners)

关于数据挖掘的概念与技术，理论与实际相结合，包括关联分析，神经网络等重要数据挖掘方法的原理与实现。(data mining)

应用MATLAB实现噪声滤波器。一段有尖锐噪声的音频信号去噪。( filter)

Tls_sprit用总体最小二乘法和旋转不变技术来估计波达方向。(Tls_sprit with total least squares and rotational invariance techniques to estimate the DOA.)

Learning Belendr persian language

史密斯圆图的应用, 包括阻抗匹配，计算方法等(Smith chart applications, including impedance matching, calculation methods)

改进粒子群算法优化BP神经网络的权值，建立BP神经网络(Improved PSO algorithm optimizes the weights of BPneural networks to establish the neural networks.)

拟牛顿法和最速下降法(Steepest Descent Methods)一样只要求每一步迭代时知道目标函数的梯度。通过测量梯度的变化，构造一个目标函数的模型使之足以产生超线性收敛性。这类方法大大优于最速下降法，尤其对于困难的问题。另外，因为拟牛顿法不需要二阶导数的信息，所以有时比牛顿法(Newton s Method)更为有效。如今，优化软件中包含了大量的拟牛顿算法用来解决无约束，约束，和大规模的优化问题。(The quasi-Newton method and the Steepest Descent Methods only require that each step iterations know the gradient of the objective function. By measuring the change of the gradient, constructing a model of the objective function is sufficient to produce superlinear convergence. This method is much better than the steepest descent method, especially for difficult problems. In addition, because the quasi-Newton method does not require information on the second derivative, it is sometimes more effective than the Newton s Method. Today, the optimization software contains a large number of quasi-Newton algorithm used to solve the unconstrained, constraint, and large-scale optimization problems.)

网上的Kalman滤波数据融合示例，此处的特点是添加了详细的注释，并且为了更容易理解和顾名思义，对部份变量和函数名作了修改，使得非常易懂。(An example of Kalman filtering data fusion on the Internet! Detailed annotations are added and some variables and function names are modified to make them easy to understand.)

Simulink仿真Simth预估器（PI控制器）(good)