RSC

matlab code for acrobat

谐波分析 功率谱分析 交叉谱分析课程及例子(The harmonic analysis of power spectrum analysis courses and examples of the cross-spectral analysis)

代码的mrics。M’是从他们的傅立叶系数的一个子集，使用总变分正则化图像重建的分裂Bregman方法的实现。使用代码指令可以在文件“mrics顶在评论中发现。”。一个演示脚本也包括在内，显示正确的使用方法。(The code ‘mrics.m’ is an implementation of the Split Bregman method for reconstructing images a subset of their Fourier coefficients using total-variation regularization. Instructions for use of the code can be found in the comments at the top of the file “mrics.m”. A demo script is also included that demonstrates proper use of the method.)

语音增强之谱相减算法，加窗分帧频域处理，计算信噪比及画出波形对比。(Spectral subtraction speech enhancement algorithm, window-frame frequency domain processing to calculate the signal-to-noise ratio and draw the waveform comparison.)

matlab 数字图像压缩 DCT实现，matlab本身有demo 但这里加固一下(digital image processing using matlab， enjoy yourself)

说明：  通过编程实现通过共轭梯度法和Gauss-Seidel迭代法两种方法求解方程组(By programming through the conjugate gradient method and Gauss-Seidel iteration method for solving equations of two)

Mean to calculate the digital filter.

地震资料 数据处理 分频去噪 模块 主要压制随机噪音 异常振幅 野值 大值 方法特点：1 针对性强，主要去除随机噪音；2 随机噪音识别能力强，达到了较高的去噪水平；3 具有自适应性，能根据不同位置的不同特点统计识别噪音；4 振幅保真，对有效信号的保护性好；5 操作者可根据经验选择参数组合灵活去噪，达到较好的结果。 应用对比：为了展示本模块的去噪效果，所选取的对比对象是某知名成熟商业软件的分频去噪模块，其去噪效果在当前诸多成熟软件模块中是佼佼者，在地震资料处理界具有很好的口碑。 通过对比，说明本模块：1 针对性强，主要去除随机噪音和异常振幅等。2 随机噪音识别能力强，达到了较高的去噪水平。3 具有自适应性，能根据不同位置的不同特点统计识别噪音。4 振幅保真，对有效信号的保护性好。5 操作者可根据经验选择参数组合灵活去噪，达到较好的结果。(Frequency-dependent noise attenuation seismic data, processing module, is mainly to suppress random noise, denoising abnormal/large amplitude values Method of characteristics: 1 targeted, mainly to remove random noise 2 random noise and strong ability to identify , reach a higher level of de-noising 3 is adaptive , able to identify the noise statistics according to the different characteristics of different positions 4 amplitude fidelity , the effective protection of the signal is good 5 denoising operator flexibility to select the combination of parameters according to the experience , to achieve better results . Application contrast: To demonstrate the effect of the de-noising module , the selected object is a well-known comparative commercial software divide mature noising module de-noising effect is the current leader in many mature software module in seismic data processing industry has a good reputation. By contrast, the description of the module : a targeted, mai)

说明：  矩阵LDLT分解与Cholesky分解 求矩阵A=（αij）20x20的LDLT分解与Cholesky分解(Matrix LDLT decomposition and Cholesky decomposition Matrix A = (αij) 20x20 of the LDLT decomposition and Cholesky decomposition)

dspace catlog for understanding