matlab_Image_Fusion_Toolkit

结构分析的有限元法与matlab程序设计3-2(Structural analysis of the finite element method and matlab programming 3-2)

基于脉冲耦合神经网络的图像边缘信息提取。基于脉冲耦合神经网络的图像边缘信息提取。基于脉冲耦合神经网络的图像边缘信息提取。(Pulse coupled neural network based on image edge information extraction. Pulse coupled neural network based on image edge information extraction. Pulse coupled neural network based on image edge information extraction.)

此项目完整玩具机器人代码和原理，还元器件清单；(This project complete toy robot code and principles, to restore the device list )

基于到达时间差(ToA)的非线性最小二乘(NLS)定位方法(Based on Time Difference of Arrival (ToA) nonlinear least squares (NLS) positioning method)

说明：  AWGN信道下高斯噪声干扰下GALILEO编码译码系统性能仿真，包括误码率仿真(AWGN channel Gaussian noise interference GALILEO codec simulation system performance, including bit error rate simulation)

拉格朗日插值法，输入x，y，再输入变量xi，就可以求得yi。(Lagrange interpolation method, the input x, y, and input variables xi, yi obtained.)

介绍了一种特定频率响应滤波器的设计方法，具有很强的实际应用价值(Introduces the design method of a specific frequency response filter, which is of great practical application value)

将newmark算法和牛顿威尔逊算法综合起来，结合两种算法的优势求解一般性动力学方程，线性和非线性都可以。(The Newmark algorithm and Newton Wilson algorithm are combined to solve the general dynamic equation, both linear and non-linear.)

matlab code for hmm understanding

传统的宽带信号中抑制正弦干扰的方法是采用陷波器(notch filter),为此需要精确知道干扰正弦的频率.然而当干扰正弦频率是缓慢变化时,且选频率特性要求十分尖锐时,则最好采用自适应噪声抵消的方法.下图是用一个二阶FIR的LMS自适应滤波器消除正弦干扰的一个方案。该代码实现了以下功能： 1) 借助MATLAB画出了滤波器的误差性能曲面和误差性能曲面的等值曲线； 2） 给出了最陡下降法以及LMS算法的计算公式； 3） 用MATLAB产生了方差为0.05, 均值为0白噪音S(n)，并画出某次采样得到的波形； 4） 根据 2）中的公式，并利用 3）中产生的S(n)，在 1）中的误差性能曲面的等值曲线上叠加画出了采用最陡下降法以及LMS法时H(n)的在叠代过程中的轨迹曲线； 5）用MATLAB计算并画出了LMS法时误差随时间n的变化曲线（对应S(n)的某一次的一次实现）和e(n)波形； 6）在 1）中的误差性能曲面的等值曲线上，叠加画出采用LMS法得到的100次实验中的H(n)的平均值的轨迹曲线； 7）最终对结果进行了分析，具体见压缩包的word文档。 (Wideband signal in the conventional sinusoidal interference suppression method is the use notch filter (notch filter), this requires precise knowledge of the frequency of a sinusoidal interference . However, when the interference frequency sinusoidal changes slowly , and the selected frequency characteristic requirements are very sharp , then best use of adaptive noise cancellation method . following figure is a second-order FIR LMS adaptive filter to eliminate a program sinusoidal interference . The code implements the following functions:   A ) draw with MATLAB error performance of the filter surface and the surface contour error performance curve 2 ) gives the steepest descent method and the LMS algorithm formula 3 ) generated using MATLAB variance of 0.05 with a mean of 0 white noise S (n), and draw a particular sampling waveform 4 ) based on 2 ) of the formula , and use 3 ) generated in S (n), in a ) the error performance curves superimposed on the surface contour pl)