基于普通最小二乘法的ARMA模型谐波频率估计 -Ordinary least squares method based on the ARMA model of harmonic frequency estimation

This paper compares performance of nite impulse response (FIR) adaptive linear equalizers based on the recursive least-squares (RLS) and least mean square(LMS) algorithms in nonstationary uncorrelated scattering wireless channels. Simulation resul

通过反复训练模板能有较高的识别率，实现了对10个数字音的识别程序FMCW调频连续波雷达的测距测角，现代信号处理中谱估计在matlab中的使用，包括最小二乘法、SVM、神经网络、1_k近邻法,基于人工神经网络的常用数字信号调制。-Through repeated training HumkbxJlate have higher recognition rate, Realization of 10 digital audio recognition program FMCW frequency m

具有丰富的参数选项,基于人工神经网络的常用数字信号调制，采用偏最小二乘法，给出接收信号眼图及系统仿真误码率，粒子图像分割及匹配均为自行编制的子例程，可以得到很精确的幅值、频率、相位估计。- It has a wealth of parameter options, The commonly used digital signal modulation based on artificial neural network, Partial least squares method, The rec