bilnsdof_response

一维波动方程的反演，和成图以及其他功能。(One-dimensional wave equation inversion, and mapping and other features.)

图1为均衡带限信号所引起失真的横向或格型自适应均衡器(其中横向FIR系统长M=11), 系统输入是取值为±1的随机序列，其均值为零；参考信号；信道具有脉冲响应： 式中用来控制信道的幅度失真(W = 2～4, 如取W = 2.9,3.1,3.3,3.5等)，且信道受到均值为零、方差(相当于信噪比为30dB)的高斯白噪声的干扰。试比较基于下列几种算法的自适应均衡器在不同信道失真、不同噪声干扰下的收敛情况(对应于每一种情况,在同一坐标下画出其学习曲线): 1）横向/格-梯型结构LMS算法 2）横向/格-梯型结构RLS算法 并分析其结果。(Figure 1 is a band-limited signal caused balanced horizontal or lattice distortion adaptive equalizer (FIR system in which the lateral length M = 11), the system input is the value of a random sequence of ± 1, mean zero reference signal channel has impulse response: Wherein the amplitude of the distortion for the control channel (W = 2 ~ 4, and so as to take W = 2.9,3.1,3.3,3.5), and subjected to a channel with zero mean and variance (equivalent SNR is 30dB) Gaussian white noise. Compare the following types of algorithm-based adaptive equalizer in a different channel distortion, the convergence of different noise interference (corresponding to each situation, draw their learning curve in the same coordinate): 1) landscape/grid- LMS algorithm ladder structure 2) landscape/grid- RLS algorithm ladder structure And analyze the results.)

一些常见的matlab源代码，参加建模的人很值得一看(Common matlab source code, it is worth a visit to participate in modeling)

//////// OFDMA //////////// No. of Subcarriers NS = 512 Input Generation x = rand(1,NS)>0.5 fftlength = 512

详细介绍了取样光栅的matlab模拟。有文字介绍源代码的编写和使用。(Details of the sampled grating matlab simulation. With text describes the preparation and use of the source code.)

useful for INS simulation

利用FOCUSS算法对数据进行重构表示，得到需要表示的成分，减少噪声干扰。(FOCUSS algorithms use the data to reconstruct said component required to obtain representation, reducing noise.)

说明：  绘制庞加莱图程序可做学习使用非线性动力学分析(Drawing a Poincare program can be used for learning Nonlinear Dynamics Analysis)

有源低通巴特沃斯滤波器设计根据给定的参数值设计有源滤波器(Active low-pass Butterworth filter design parameters according to the given active filter design)

用MATLAB实现FIR，包括常用窗函数代码(Using MATLAB FIR, including the commonly used window function code)