整理好的IDW距离反比加权方法matlab代码

瑞萨数据手册指令集瑞萨数据手册指令集瑞萨数据手册指令集(zhilingji)

详解MATLAB数字图像处理(张德丰)[程序源代码](Detailed MATLAB digital image processing (Zhang Defeng) [source code])

采用数据拟合法进行的高斯白噪声信道下的信噪比估计，程序中有经典summer法以及本人自己拟合的二阶和三阶参数，适用于不同的信噪比范围，望大家一起交流(By data fitting of the Gauss white noise channel SNR estimation, the program in the classic summer method as well as my own fitting of the two order and three order parameters, applicable to different SNR range, hope everybody exchanges together)

通过MATLAB编程，实现模拟退火算法的功能，一次实现TSP问题。(Through MATLAB programming, to achieve the function of simulated annealing algorithm, a TSP problem.)

利用matlab程序设计出匹配滤波器的功能源码(Procedures designed to use matlab function of matched filter source)

说明：  在MATLAB环境下进行双线性变换椭圆低通滤波器设计(In the MATLAB environment bilinear transform elliptical low-pass filter design)

使用统计中值法，获取背景图像。简单易懂，希望对大家有帮助。(Using the statistical value method, to obtain the background image. Easy to understand, we hope to help.)

matlab 最优化处理的一些简单编程，以及附带若干个例子(Some simple matlab program optimization, and with some examples)

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. )

说明：  讲kalman滤波及其matlab应用的书 经典 详尽(kalman filtering using matlab)