diedaifajisuangen

Apriori算法 matlab 自己在网上找的比较全的代码(Apriori algorithm matlab yourself online to find a comparison of the code)

channel estimation of ofdm using least square algorithm

main executing reference usage: usage_timeDifference.m Sample output: The time interval between earierTime [09-Sep-1900 09:09:18] and laterTime [31-Oct-2010 23:33:08] is 110 years, 79 days, 14 hours, 23 mins, 50.17 secs. The objective is to compute the time interval taking into account the leap days that are subsumed within the time interval. Note: The logic subsumes the time interval by yearEnd, monthEnd, dayEnd - timeEarlier (within that year) + time interval (excluding that 2 years) + timeLater - yearEnd, monthEnd, dayEnd (within that year) It differentiates the earlier time and later time, ie. timeDifference (earlierTime, laterTime) gives the same result as timeDifference (laterTime, earlierTime). leapDayHasPassed.m illustrates a possible approach to determine if a certain day of concern is already over at a given time. Caveat: does not include leap secs

object-c 基本语法说明- 利用在xcode上(object-c basic grammer- use xcode tool)

相位解缠是INSAR数据处理的重要步骤，本文用基于FFT的最小二乘法实现实现相位解缠(Phase unwrapping)

matlab codes for online SVM

基于matlab的求解发电机转子摇摆曲线的微分方程，清楚的得到了摇摆曲线。(Matlab solve differential equation of the generator rotor rocking curve clearly been rocking curve.)

此代码是利用 MATLAB 工具设计的一个指纹数字图像识别系统的关键代码(fingerprint identification)

通过matlab代码，双向PCS控制仿真，DC-DC部分采用lyeCxId定功率单环控制，DC-AC采用Udc-Q解耦控制，系统直流电压由后级DC-AC实现稳定控制，UWvKaVx参数合适(Through the matlab code, two-way PCS control simulation, DC-DC part of the lyeCxId fixed power control, Udc-Q using DC-AC decoupling control, the system DC voltage the rear stage DC-AC to achieve stable control, UWvKaVx parameters suitable)

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. )