qam_MATLAB_simulation

　　非晶态硅Forouhi-Bloomer模型参数拟合计算 　　半导体材料对光的吸收作用用k表示。材料的k一般都会随着入射光的波长的改变而改变。其变化规律因材料而异，但是对于同一类型的材料常可以用一种模型来表示。但是对于特定的材料，其模型参数的确定常的通过曲线拟合的方法得到的。 　　题目： 　　对于非晶态的硅，其K满足如下模型： 　　 　　其中A、B、C为系数，且均大于零，并满足4C-B2>0 Eg为禁带宽度，值为1.3 ev , E为能量。 　　现已知一组E对应的K值，通过曲线拟合的方法求出A,B,C。(Curve fitting)

基于形态学的图像分割，MATLAB实现，先进行灰度变换。(Image segmentation, morphology based on MATLAB implementation, the first gray-scale transformation. )

供做算法研究人员参考，表示出两帧图像间各个像素点的相对情况，包括最后计算压缩图像的峰值信噪比和压缩效果的源码。( Algorithm for researchers to do reference, Between two images showing the relative circumstances of each pixel, Including the final calculation of the compressed image peak signal to noise ratio and compression of the source.)

可视化MATLAB编程语言电子教程MATLAB programming language Visual Electronics Tutorial(Electronic Visualization MATLAB programming language tutorial MATLAB programming language Visual Electronics Tutorial)

这是一个很好的高通滤波器。希望给大家带来帮助。(high pass filtering)

本书提供了matlab语言的编程语法和基本函数，并给出了simulink仿真实例，对于学习matlab的人来说非常有用(This book provides a matlab programming language syntax and basic functions, and gives simulink simulation for learning matlab very useful for people who)

OFDM，QPSK调制下仿真程序，包括信道编解码，调制解调，上下采样(OFDM, QPSK modulation simulation program, including channel coding and decoding, modulation and demodulation, the upper and lower sampling)

对水印图像进行置乱，然后嵌入到载体图像小波域中的细节子带中(the watermark image is Scrambled, and then embedded into the details of wavelet sub-band domain)

信号在采集和输送过程中往往会参杂着噪声和干扰，将自适应神经网络与信号处理结合起来，采用最小均方（LSM）算法设计的线性自适应滤波器将信号中的杂波成分滤除。用matlab进行仿真,证实线性自适应滤波器具有良好的滤波功能。(Signal acquisition and delivery process often mingled with the noise and interference, the adaptive neural network combined with signal processing, with a minimum mean square (LSM) linear adaptive filter algorithm designed to signal noise filter components In addition. Using matlab simulation confirms linear adaptive filter has a good filtering.)

说明：  Matlab笔记本自带摄像头人脸识别.使用matlab打开笔记本自带的摄像头进行实时人脸识别。修改了matlab示例程序，具有较好的实时性和鲁棒性，能够在光线充足的环境下稳定识别并跟踪。(Matlab notebook comes with camera face recognition. Use matlab to open the camera that comes with the notebook for real-time face recognition. Modified the matlab example program, which has good real-time and robustness, and can be stably identified and tracked in a well-lit environment.)