generation

Most recent approaches have posed texture synthesis in a statistical setting as a problem of sampling from a probability distribution. Zhu et. al. [12] model texture as a Markov Random Field and use Gibbs sampling for synthesis. Unfortunately, Gibbs sampling is notoriously slow and in fact it is not possible to assess when it has converged. Heeger and Bergen [6] try to coerce a random noise image.

matlab最小值,用于求一组数据中的最小值。(min function of matlab)

信号与信息处理——阵列信号处理DOA估计的matlab算法，这是线性调频信号的稀疏分解算法，wigner_will分布(Signal and information processing- array signal processing matlab algorithm for DOA estimation, which is a linear FM signal sparse decomposition algorithm, wigner_will distribution)

MASReperageSecteur simulation of sector it is used for controling the inverters switch

说明：  使用MATLAB进行时间序列分析及建模与预报(Time series analysis and modeling and forecasting)

learning matlab student version

Wavelet denoising For using this code need to use signal toolbox and general toolbox in your matlab In the first part of this assignment, we asked to obtain a (black-and-white) digital image of size 512 by 512 and then generate noisy image by adding a Gaussian noise but under the condition of having SNR=20dB by select the suitable value of variance for Gaussian noise formula. Second step is performing wavelet denoising using the hard thresholding (Use the db 6 for four levels) in the condition of finding the optimal thresholding value of T in terms of the SNR obtained. It means that, we should find the highest SNR value by finding the suitable value for threshold. Then we asked to do the same process but this time using soft thresholding. Finally for the last part of question one, we should compare the results of the obtained SNR with the recommendations of 3*sigma for the hard thresholding and 3/2*sigma for the soft thresholding.

Simple model of FSK decoder

Windows Azure中的多层带表，队列和斑点应用(Windows Azure Multi-Tier Application with Tables, Queues, and Blobs)

对语音信号加入窄带噪声并用小波去除噪声并显示结果(add narrowband noise to signal and decrease it with wavelet)