adaptive--filter--noise-

自组织特征映射模型(Self-Organizing feature Map)，认为一个神经网络接受外界输入模式时，将会分为不同的区域，各区域对输入模式具有不同的响应特征，同时这一过程是自动完成的。各神经元的连接权值具有一定的分布。最邻近的神经元互相刺激，而较远的神经元则相互抑制，更远一些的则具有较弱的刺激作用。自组织特征映射法是一种无教师的聚类方法。(Self-organizing maps model (Self-Organizing feature Map), that a neural network to accept outside input mode, will be divided into different regions, the regional input modes have different response characteristics, while the process is done automatically . The connection weights of neurons with a certain distribution. Nearest neurons stimulate each other, while distant neurons are mutually inhibitory, with a further some of the weaker stimulus. Self-organizing feature map method is a clustering method without teachers.)

基于QPSK和16QAM的OFDM仿真程序(OFDM simulation based on 16QAM and QPSK modulation)

五个经典matlab仿真实例，由易到难，初学者的学习法宝(Five classic matlab simulation examples, easy to difficult, for beginners to learn magic)

matlab PID simple s model pid最简单的S模型，可以自己加入扫频信号，就可以看开环伯德图了(matlab PID simple s model)

研究表明超高斯分布更加贴近语音信号的实际分布，然而语音信号很难用单一的概率密度 函数准确描述，针对这一情况，提出了一种用超高斯混合模型对语音信号幅度谱建模的新方法，并推导了 基于此模型的幅度谱最小均方误差估的估计式。仿真结果表明：与传统的短时谱估计算法相比，该算法不 仅能够进一步提高增强语音的信噪比，而且可以有效减小增强语音的失真度，提高增强语音的主观感知 质量。 (Recent research indicates that the speech spectral amplitude distributions could be fairly described with super-Gaussian probability density function. However, the complexity of speech signal determines that the distribution statistics ofspeech signal could not be well described by single simple function. Thus a super-Gaussian mixture model for speech spectral amplitude is proposed, and with this model, a minimum mean-square error (MMSE) estimator for speech signals spectral amplitude is derived. The simulation results show that this algorithm based on Gaussian and super-Gaussian speech model could achieve better noise suppression and lower speech distortion as compared with the conventional short-time spectral amplitude estimation algorithm. )

CSI in a channel no awgn

说明：  高斯、泊松、瑞丽分布是信道中噪声最基本的几种分布到情况，了解信道噪声情况对于信道去噪是很有必要的(it is very important in the processing of denoising)

its about matlab books

说明：  一个用DBN做时间序列预测的实例，内包括了数据(An example of using DBN to predict time series includes data)

对答题卡考生考号进行识别，对图片进行灰度，切割处理，其中有部分实用对网站的建设。(Candidate number on the answer sheet to identify candidates, on the image to gray scale, cut processing, in which some practical construction of the site.)