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4QAM、16QAM、32QAM、64QAM、128QAM、256QAM星座图映射，map、频偏估计算法(4QAM, 16QAM, 32QAM, 64QAM, 128QAM, 256QAM constellation mapping, map, frequency offset estimation algorithm)

eps value fitting function eps = hw1(e) if ((1+e) <= 1) e = e * 2 else e = e / 2 hw1(e) end eps = e (eps value fitting function eps = hw1(e) if ((1+e) <= 1) e = e* 2 else e = e/2 hw1(e) end eps = e )

基于MATLAB的齿轮箱振动故障诊断的程序(Gearbox vibration fault diagnosis based on MATLAB program)

说明：  简要阐述BPSK调制解调原理 用MATLAB进行仿真，附上仿真源程序和仿真结果，对结果进行分析。(The principle of BPSK modulation and demodulation is briefly described Matlab is used for simulation. The simulation source program and simulation results are attached to analyze the results.)

汉明码仿真 ７４汉明码 包括编码解码( The hamming code imitates really)

LDPC MATLAB 仿真源程序，希望对您有用(LDPC MATLAB simulation source, hope useful for you)

Most countries are facing a multiplicity of challenges directly related to the pr ent ways in which they currently generate and use energy. Human-induced climate change, rising pollution levels, decreasing energy security, and resource wars are all increasingly linked to the widespread use of non-renewable sources of energy. These interrelated challenges present an ongoing and pressing policy-making dilemma to develop and implement sound energy solutions. Evidence regarding the imperative need for creative energy solutions is amassing a variety of reputable sources. The Fourth Assessment Report by the Intergovernmental Panel on Climate Chance (IPCC) ranks amongst the most salient of these sources. This IPCC report clearly points out that drastic reductions in the use of fossil fuel use are essential to reduce greenhouse gas (GHG) emissions to thereby minimize the most detrimental impacts of climate change.

利用Matlab产生各种回声、击掌等特殊效果的音频程序。(Matlab, generate a variety of echo, clap audio programs and other special effects.)

针对SVM法线特征筛选算法仅考虑法线对特征筛选的贡献,而忽略了特征分布对特征筛选的贡献的不足,在对SVM法线算法进行分析的基础上,基于特征在正、负例中出现概率的不同提出了加权SVM法线算法,该算法考虑到了法线和特征的分布.通过试验可以看出,在使用较小的特征空间时,与SVM法线算法和信息增益算法相比,加权SVM法线算法具有更好的特征筛选性能.(Normal feature selection for SVM algorithm only considered normal for the contribution of feature selection, to the neglect of the characteristics of the distribution of feature selection have contributed to the lack of normal SVM algorithm based on the analysis, based on the characteristics of the positive and negative cases emergence of a different probability-weighted normal SVM algorithm, which takes into account the distribution and characteristics of normal. through the test can be seen in the use of smaller feature space, the normal and the SVM algorithm and information gain algorithm, normal weighted SVM algorithm has better performance of feature selection.)

利用matlab的基本方法，求出矩阵的逆，体现matlab的矩阵功能。(Matlab using the basic method to derive the inverse matrix, the matrix reflect the matlab function.)