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It calculates a Thiran filter for fractional delay

To keep overall output power per unit cost low, the grid-connected converters should be able to extract the maximum available power from the PV arrays. Since the PV array characteristic is highly nonlinear, maximum power point tracking (MPPT) of the PV arrays becomes rather challenging.

牛顿-柯特斯数值积分公式及其MATLAB的实现 复化Newton-Cotes数值积分公式 (Newton- Cotes numerical integration formula and the MATLAB implementation of complex numerical integration of Newton-Cotes formulas)

一种遗传算法的MATLAB实现代码，调试过的(A genetic algorithm realize MATLAB code, debug off)

i have wote a matlab code to track human in vidoe and this is well runing but i need a code for huma detection in maltab if anyone have thenm plz mail me on my adrees

该程序是一个仿真模型，对窄带的带通滤波器进行了仿真(The program is a simulation model of narrow band pass filter was simulated)

说明：  利用 matlab 分别基于 ACF 和 W-AMDF 求基音频率，程序均调试通过。其中的 word 文档为下载资源，供大家参考对比(compute fundamental frequency of speech signal base on ACF and W-AMDF respectively, while the download word document for your reference.)

说明：  仿真实现了十三位巴克码进行脉内调相。很好的程序，亲自优化过。(Thirteen Barker codes are simulated for intra-pulse phase modulation. Good procedures, personally optimized.)

duffing方程用于微弱信号检测的matlab程序。包含两种方法，一种是inline，一种是@fan。(duffing equation for weak signal detection matlab program. Contains two methods, one is inline, one is @ fan.)

传统的短时谱估计语音增强算法通常假设语音谱分量相互独立，没有考虑语音谱分量间的相关性。针对这 一问题，该文提出一种新的基于多元Laplace分布模型的短时谱估计算法。首先，假设语音的离散余弦变换(DCT) 系数服从多元Laplace分布，以此利用谱分量间的相关性；在此基础上，利用多元随机矢量的高斯尺度混合模型表 示，推导得到语音DCT系数矢量的最小均方误差(MMSE)估计的解析表达式；并进一步推导了基于该分布模型的 语音存在概率，对最小均方误差估计子进行修正。实验结果表明，该算法在抑制背景噪声和减少语音失真等方面优 于传统的语音增强方法。(The spectral components of speech are usually assumed to be independent in traditional short-time spectrum estimation, which is not the case in practice. Tosolve this problem, a new speech enhancement algorithm with multivariate Laplace speech model is proposed in this paper. Firstly, the speech Discrete Cosine Transform (DCT) coefficients are modeled by a multivariate Laplace distribution, so the correlations between speech spectral components can be exploited. And then a Minimum-Mean-Square-Error (MMSE) estimator based on the proposed model is derived using a Gaussian scale mixture representation of random vectors. Furthermore, the speech presence uncertainty with the new model is derived to modify the MMSE estimator. Experimental results show that the developed method has better noise suppression performance and lower speech distortion compared to the traditional speech enhancement method. )