mf_var_0-1lzowdx

用双线性变换法设计IIR数字滤波器 （1）用双线性变换法设计一个巴特沃斯低通IIR 数字滤波器。设计指标参数为：在通 带内频率低于0.2π 时，最大衰减小于1dB；在阻带内[0.3π ,π ] 频率区间上，最小衰减大于15dB。 （2）以0.02π 为采样间隔，打印出数字滤波器在频率区间[0,π / 2] 上的幅频响应特性 曲线。 （3）用所设计的滤波器对实际心电图信号采样序列（在本实验后面给出）进行仿真滤 波处理，并分别打印出滤波前后的心电图信号波形图，观察总结滤波作用与效果。 (err)

matlab工具箱，SVM。。。支持向量基(matlab toolbox, SVM. . . Support vector-based)

本程序实现深度学习的卷积神经网络（CNN）算法，含有训练程序和测试程序(This program implements convolution depth learning neural network (CNN) algorithm contains training programs and test procedures)

这是东南大学信息科学与工程学院《数字信号处理 第二版》第四章的实验，关于IIR 滤波器的( This is the School of Information Science and Engineering, " Digital Signal Processing Second Edition" Southeast University experiment of Chapter IV, on IIR filters)

灰色预测 GM（1,1） 灰色关联 matlab 数学建模(graysystem matlab)

基于模态振型的固定结合面动态特性参数测试 (Based on a fixed mode shapes combined with dynamic characteristic parameters of the test surface)

判断下列方阵是否可对角化，是否为正定二次型（顺序主子式判断法、特征值判别法）(using MATLAB to determine if a the matrix is diagonalizable，if the real vector space is definite quadratic)

本程序模拟光的干涉现象：杨氏双缝干涉，劈尖干涉和牛顿环干涉，并计算光的光强分布，另外，附有相应的仿真图(MATLAB for three types of interference of light and calculate the intensity of the and have corresponding figures)

matlab传染病sis及相关模型的图的模型，及运用(Matlab infectious disease sis and related model diagram model, and application)

time-invariant degradation models and stationary signals and noise, the classical Fourier domain Wiener filter, which can be implemented in O(N logN) time, gives the minimum mean-square-error estimate of the original undistorted signal. For time-varying degradations and nonstationary processes, however, the optimal linear estimate requires O(N2) time for implementation. We consider filtering in fractional Fourier domains, which enables significant reduction of the error compared with ordinary Fourier domain filtering for certain types of degradation and noise (especially of chirped nature), while requiring only O(N logN) implementation time. Thus, improved performance is achieved at no additional cost. Expressions for the optimal filter functions in fractional domains are derived, and several illustrative examples are given in which significant reduction of the error (by a factor of 50) is obtained.