New-folder-(2)

the fuzzy c means program !!

十字交叉阵的波束形成，crossarray beamform(crossarray beamform)

程序利用小波分解将声音信号分解为高频与低频部分，而后利用软阈值方法确定高频与低频各自的小波重构系数，将高频与低频部分重构还原信号达到降噪的目的。(Program using wavelet decomposition sound signal into high and low parts, then use soft threshold method to determine the high and low frequency coefficients of each wavelet reconstruction, reconstruction of the high and low frequency part of the purpose of noise reduction signal reaches.)

这是一个matlab程序，其中包括初始化程序，QAM程序，OFDM主程序，以及发送接受，串并转换等各部分的说明，各个部分一目了然。(This is a Matlab procedures, including the initialization procedures, QAM procedures, OFDM main program, and this acceptance, and series such as the conversion of the note, the various parts transparent.)

改进的总体经验模态分解,效果不错,欢迎讨论(Improved overall empirical mode decomposition, the effect is good, welcome to discuss)

永磁同步风机 并网 控制 仿真实例，可用于实际工程算法和研究学习(Permanent magnet synchronous wind turbine and grid control simulation example, can be used for practical engineering algorithms and learning)

circle fitting to find damping

说明：  灰度膨胀和腐蚀，matlab源程序，在matlab本身函数的基础上进行改进(Gray-scale expansion and corrosion, matlab source, in the matlab function itself on the basis of improved)

针对感应电机扩展卡尔曼滤波器转速估计中难以取得卡尔曼滤波器系统噪声矩阵和测量噪声矩阵最优值的问题，提出了一种基于改进粒子群算法优化的扩展卡尔曼滤波器转速估计方法。算法通过融合遗传算法和粒子群算法的优点，采用可调整的算法模型对粒子群算法进行改进，将改进的粒子群算法对扩展卡尔曼滤波器中的系统噪声矩阵和测量噪声矩阵进行优化处理，将优化后的卡尔曼滤波器应用于感应电机转速估计。( Extended Kalman Filter for induction motor speed estimation problem is difficult to obtain a Kalman filter system noise matrix and the measurement noise matrix optimal value proposed speed estimation method based on improved particle swarm optimization of the extended Kalman filter. By virtue of the genetic algorithm and particle swarm optimization algorithm fusion algorithm using the adjustable model PSO improvements that will improve the PSO extended Kalman filter system noise matrix and the measurement noise matrix optimization process, the optimized Kalman filter is applied to the induction motor speed estimate.)

通过非线性模型UNGM比较mlp与ekf算法的性能(Comparison mlp by non-linear model UNGM performance of the algorithm with the ekf)