subplot

FastTools，比系统自带的Vlookup sum自带的快多啦！！(FastTools, a lot faster than the Vlookup sum comes with a built-in system!!)

相位对准技术，用多正弦波进行相位的校准，给出了最小均方误差的仿真图形(phase_detrending)

基于matlab的语音回波抵消系统仿真设计中A/D转换部分程序(Voice echo cancellation system based on matlab simulation in the design of A/D conversion part of the program )

BP神经网络识别手写字符验证码，包括10721张字母、数字样本(BP neural network handwritten character recognition codes, including 10,721 letters, numbers, samples)

simulink的教程其中包括matlab三章讲解和simulink有六章讲解，详细的例子说明(matlab simulink)

光纤陀螺误差建模与分析，北航惯性导航基础课程大作业，含matlab程序代码(FOG error modeling and analysis, Northern-based inertial navigation operations courses, including matlab code)

小波分析理论与MATLAB7实现，是本电子书，需要安装超星电子图书阅读器来阅读。(Wavelet analysis theory and MATLAB7 realization is the e-books, need to install Superstar electronic book reader to read.)

基于自组织特征映射神经网络的图像压缩算法，ＥＩ检索论文，绝对有参考价值．(Based on self-organizing feature map neural network image compression algorithm, EI retrieval papers, the absolute reference value.)

说明：  程序1：遗传算法和非线性规划函数的优化； 程序2：基于遗传算法的BP神经网络优化； 程序3：基于遗传算法的TSP算法； 程序4：基于遗传算法的LQR控制器优化设计 程序5：基于遗传算法的函数优化(Program 1: genetic algorithms and nonlinear programming function optimization Program 2: Based on the genetic algorithm BP neural network optimization Program 3: TSP algorithm based on genetic algorithm Program 4: LQR controller based on genetic algorithm optimization procedures 5: Function Optimization Based on Genetic Algorithm)

共振解调的过程如下：首先对采集到的信号进行傅里叶变换，然后利用传感器自身的谐振频率进行分析，对滤波后的信号进行包络，包络以后去除了高频部分，得到包络信号，再对改进的包络信号进一步进行低通滤波，最后对最终得到的信号进行傅立叶变换求其频谱图。共振解调的原理及其过程可以用图2 来进行表述。(The process of resonance demodulation is as follows: First, Fourier transform is performed on the collected signal, and then the resonance frequency of the sensor is used for analysis. The filtered signal is enveloped, and the high frequency part is removed after enveloping to obtain an envelope. The signal is further subjected to low-pass filtering on the improved envelope signal. Finally, the spectrum of the resulting signal is Fourier-transformed. The principle of resonant demodulation and its process can be expressed in Figure 2.)