pmsm

square wave inverter dc to ac conversion

用MATLAB语言将3-PSS并联机器人的工作空间表示出来 利用数值搜索法(MATLAB 3-PSS ROBOT workspace)

计及储能的风电系统系统风险评估，参数齐全可直接使用(Risk assessment of wind power system considering energy storage)

可以识别二维的条形码。读入条形码图像之后即可处理成相应的数字。但是对图像存储位置有要求，所以请按照程序前面的存储位置放置您的二维图像(Can identify the two-dimensional barcode. Reads the barcode image can be processed into a corresponding digital. But the image storage location requirements, so please be placed in accordance with the storage location of the program in front of the two-dimensional image)

格-梯型结构的LMS算法，按照最小均方准则，设计出阶数和时间分别递推的自适应滤波器，可以进行梯型滤波，又具有格型预测前后节独立、收敛快速的优点，但计算量大。(Grid- LMS algorithm in a ladder-type structure, in accordance with the minimum mean square criterion, design order and time adaptive recursive filter, ladder filter, and lattice prediction independent front and rear section, and fast convergence.but computationally intensive.)

ga 派車路徑排班，執行有詳細步驟點選說明(ga派车path scheduling, implementation steps detailed description click on)

关于分数阶傅里叶变换的例子关于分数阶傅里叶变换的例子关于分数阶傅里叶变换的例子关于分数阶傅里叶变换的例子(the example of frathinog fft)

仿真4-PAM（脉冲幅度调制）载波调制信号在AWGN（加性高斯白噪声AWGN(Additive White Gaussian Noise)）信道下的误码率和误比特率性能，并与理论值相比较。(Simulation 4-PAM (pulse amplitude modulation) modulation signal in AWGN (additive white Gaussian noise AWGN (Additive White Gaussian Noise)) under the channel bit error rate and bit error rate performance, and compared with the theoretical value.)

卡尔曼滤波原理及程序手册，非常好用，非常方便(Kalman filtering principles and procedures manual, very easy to use, very convenient)

We address the problem of blind carrier frequency-offset (CFO) estimation in quadrature amplitude modulation, phase-shift keying, and pulse amplitude modulation communications systems.We study the performance of a standard CFO estimate, which consists of first raising the received signal to the Mth power, where M is an integer depending on the type and size of the symbol constellation, and then applying the nonlinear least squares (NLLS) estimation approach. At low signal-to noise ratio (SNR), the NLLS method fails to provide an accurate CFO estimate because of the presence of outliers. In this letter, we derive an approximate closed-form expression for the outlier probability. This enables us to predict the mean-square error (MSE) on CFO estimation for all SNR values. For a given SNR, the new results also give insight into the minimum number of samples required in the CFO estimation procedure, in order to ensure that the MSE on estimation is not significantly affected by the outliers.