Modulation-Demonstrate

matlab 俄罗斯方块用于你的个人程序的设计和开发(MATLAB)

说明：  运用Matlab模拟波动光光学的实验现象，包括小孔衍射，单缝衍射，双缝衍射，分振幅，分波面干涉，以及多光路干涉。(Matlab simulation of fluctuations in the use of optics experiments, including holes diffraction, single-slit diffraction, double-slit diffraction, sub-amplitude, sub-wave-front interference, and a number of optical interference.)

using matlab, for prediction systems

说明：  高通滤波的matlab程序的实现代码matlab程序(High-pass filter matlab program implementation code)

build your own reptilian robot

Title : Implementation of quadrature modulation and demodulation Design Object : By implementing quadrature modulation and demodulation of analog signals in digital signal processing, students will have better understanding of sampling and frequency analysis of discrete-time signals. Design Content : Make a MATLAB function which performs quadrature modulation and demodulation for a input signal with anti-aliasing filtering.

灰色预测程序，采用GM(1,1)模型建立(Grey prediction program)

实例10：阶梯图 实例11：枝干图 实例12：罗盘图 实例13：轮廓图 实例14：交互式图形 实例15：变换的傅立叶函数曲线(Example 10: Ladder Diagram Example 11: Example branches Figure 12: Compass Chart Example 13: The contour map instance 14: 15 Interactive graphic example: the Fourier transform function curve)

以实际所测随机中子脉冲数据的自相关函数为研究对象，借助仿真实验，开展Elman神经网络对不同浓度核材料进行识别的研究。在实测数据的基础上，通过叠加随机噪声，模拟产生了不同浓度核材料的相关函数样本用于神经网络的训练与测试，实验结果表明，(Calculating the stochastic neutron pulse autocorrelation function with the actually measured data as the research object, we carry out different simulate experiments in concentration identification of varied nuclear materials using Elman neural network. Superimposing random noise on the measured data, we get correlation function samples simulating the different concentrations of nuclear material for training and testing the neural network.)

此为进行独立成分分析(ICA)的matlab代码，盲源分离(BSS)是指在不知源信号和传输通道的参数的情况下，根据输入源信号的统计特性，仅由观测信号恢复出源信号各个独立成分的过程。这一过程又称为独立成分分析(ICA)。(This is the independent component analysis (ICA) of the matlab code, Blind Source Separation (BSS) is not knowing the source signal and transmission channel parameters, according to the statistical characteristics of the input signal, only the observation signal to restore the source signal The process of each individual component. This process is also known as Independent Component Analysis (ICA).)