creat_ntw

该程序是通过MATLAB平台作出的修正型平面二次包络蜗杆的仿真图.(The program is made through the MATLAB platform modified Planar Double-Enveloping Worm Simulation Fig.)

说明：  多通道同步挤压算法，MSST，提高时频图的频率精度(Multi-channel synchronous extrusion algorithm, MSST, improves the frequency accuracy of time-frequency graph)

谱分析的源程序，适合通信等专业的初学者学习使用，希望给需要的人帮助(Spectral analysis of the source, suitable for beginners to learn communication and other professional use, I hope to those who need help)

matlab实现升余弦滤波，已通过测试，可运行！(Raised Cosine Filtering)

input: fun x(t) t min & t max a df T = t_max-t_min fs = a*1/T 输入1：方程，xt；输入2，3：信号起始时间；输入4：选取的采样周期是信号长度倒数的倍数， 默认为50；输入5：频域分辨率，默认为0.3 输出频域信号和频域范围 为了提高fft的速度，频域信号长度是2的次方( Input: fun x (t) t min & t max a df T = t_max-t_min fs = a* 1/T Input 1: Equation XT input 2,3: signal start time input 4: select the sampling period is the reciprocal multiples of the signal length, default is 50 input 5: frequency domain resolution, default is 0.3 of the output frequency domain signal and the frequency domain in order to improve the speed of the FFT, the frequency domain signal length is a power of 2)

数据白化处理matlab程序，内有注释，简单易懂，适用于初学者(Data whitening processing matlab program with annotations)

说明：  普林斯顿大学无线通信著名教授Verdu的经典代表作，绝对的好书！(Princeton University Professor Verdu wireless communications known classical masterpieces, absolute good book!)

机械设计及理论 转子动力学中对轴承的研究(Mechanical Design and Theory Rotor Dynamics)

Is a group of GUI files (MATLAB), this permit load and save differents mathematical functions and plots this

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)