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人工神经网络进行数字卡片识别，Matlab环境(Artificial neural network for digital identification card)

大家看看，关于最优单纯形法非线性方程matlab源代码(We can see that on the optimal simplex method matlab source code. . .)

【matlab编程代做】水平集模型的图像分割 ([Do] matlab programming generation level set image segmentation model)

半带滤波器的matlab实现，实现了2倍抽样的过程。(Half-band filter matlab implementation, to achieve a 2-fold sampling process.)

MATLAB中的语音信号分帧， 语音分析中的窗函数， 语音信号短时时域处理， 语音信号短时频域处理(MATLAB voice signal framing, Voice analysis window function, Short time-domain speech signal processing, Short speech signal in the frequency domain processing)

基于语音信号处理的MATLAB平均幅度差函数，比自相关函数计算量要少。(Based on the average amplitude of the speech signal processing functions, less than the autocorrelation function computation.)

基于Matlab，利用小波变换进行图像去噪(Image de-noising based on wavelet transform)

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, and down sampling)

此代码是基于DCT的数字水印MATLAB编程，包括水印的置乱和反置乱，嵌入以及提取水印四个部分(This code is based on digital watermark DCT MATLAB programming, including the watermark scrambling scrambling and anti-, four-part watermark embedding and extraction)

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.)