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perl program guide ch1

this is simple qpsk for matlab code

基于matlab的16QAM调制源代码，并进行的误码分析(Based on the 16QAM modulation matlab source code, and error analysis carried out by)

降维的mimo测向算法，基于music算法的mimo侧向算法 (reduced dimensional music algorithm)

训练错误率和交叉验证错误率相等，在样本比较大时，这个结果是可以预期的；训练错误率一般低于测试错误率，但是当样本数据比较少时，实验也出现了意外，样本多的那组测试错误率比样本少的训练错误率还要小；在本实验中，同组数据的交叉验证错误率比独立测试错误率高，这个反常现象是因为样本的原因所致，交叉验证的样本小，而独立测试时所用训练样本数目大，因而出现这种情况。分类线上，fisher准则是一条直线，而贝叶斯分类器实际上是一个类似椭圆的封闭曲线；很明显，贝叶斯分类器比fisher分类器要好。(Training error rate and cross- validation error rates are equal, the larger the sample , this result is to be expected training error rate is generally lower than the test error rate , but when comparing the sample data came from the experiment there was an accident, that more samples group test error rate less than the training sample error rate is smaller In this experiment, the same set of data cross-validation error rate than independent test error rate, this anomaly is because the sample of reasons , cross-validation sample is small,And independent testing large number of training samples used , resulting in this situation.Classification online , fisher criterion is a straight line , while the Bayesian classifier is actually a closed curve similar to elliptical It is clear that the Bayesian classifier is better than the fisher classifier .)

针对DEM的建模问题，将高程看作区域化变量，应用地质统计学中普通克里格研究了一个山区高程空间变异分析及其插值。(DEM for modeling will be seen as a regionalized variable elevation, application of ordinary kriging in geostatistics research a mountain elevation spatial variability analysis and interpolation.)

用希尔伯特黄变换（HHT）求时频谱和边际谱.包括代码、原理、截图分析(Hilbert Huang transform (HHT) Find the spectrum and marginal spectrum, including the code, schematic, screenshot analysis)

卷积编码的matlab的S函数程序,对使用simulink者有很大帮助,程序已验证.(Convolutional coding of the S function matlab procedures on the use of simulink who have great help, the program has been verified.)

mmse接收 不错的程序,希望能够给大家参考(mmse receiving good procedures, we hope to be able to make reference to)

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.