FBMC_UFMC_OFDM_5G-master

文章展示了基于高斯混合模型的语音频谱预测方法。频谱预测可能在传包过程中预防丢包这方面起到大作用。期望最大化算法用两倍或三倍的连续语音因素来测试模型。模型被用来设计第一，儿等指令预测量。预测表用频谱分配状态来估计并和一个简单的参考模型对比。最好的预测表得到一个平均频率扭曲值是0.46dB小于参考模型(This paper presents methods for speech spectrum prediction based on Gaussian mixture models. Spectrum prediction may be useful in a packet transmission system where the sensitivity to packet losses is a major problem. Models of speech are trained by the Expectation Maximization algorithm using pairs, triples etc. of consecutive cepstral vectors. The models are used to design first, second etc. order predictors. The prediction schemes are evaluated using the spectral distortion criterion and compared to a simple reference method. The best prediction scheme obtains an average spectral distortion that is 0.46 dB less than for the reference method. )

generate music signal

【谷速软件】多级树集合分裂（SPIHT）图像压缩算法源代码 可以做为参考使用 ([Software] Valley speed multilevel tree collection division (SPIHT) image compression algorithm source code can be used as a reference to use)

This is Photo Studio template

遗传算法优化后计算潮流的一个改进程序，给大家看看(Genetic algorithm optimization of a trend of improvement after the calculation procedure for everyone to see)

图像处理MATLAB源代码，这个是哈夫曼编码(huffman)

采用动态加权综合评价方法建立评价模型，增大了评价结果的客观性。首先对评价指标数据进行归一化处理，然后选取偏大型正态分布函数作为动态加权函数建立评价模型，从而对评价指标观测值进行排序，最后用决策(Dynamic weighted comprehensive uation method to establish uation model, increasing the objectivity of uation results. First uation data normalization, and then the partial large normal distribution function as a dynamic weighting function uation model, and thus the uation observations are sorted, with the final decisions)

Lossy Run Length coding and decoding

压缩包中的一系列matlab程序实现了“特定人群语音情感识别”这一新颖的研究课题。具体介绍请见压缩包中的论文。(compressed in a series of Matlab program of "specific emotional crowd voice recognition" of the new study. Specific details of compressed see the papers.)

说明：  电力系统中的牛顿拉夫逊算法实现潮流计算，Matlab实现，可以直接读取数据，目前110节点适用(Power System Newton Raphson power flow algorithm, Matlab implementation, you can read the data for the current node 110)