data-input-and-export

malarial detention parasites related matlab code you can find image segmentation techniques

Quasi-Orthogonal Space-Time-Frequency Trellis Codes for MIMO-OFDM Systems

DBN源码，深度学习领域的适合初学者学习的代码之一，基础必备的内容。(DBN source, depth of learning areas for beginners to learn the code, one basic essential content.)

以matlab编写的pi-sigma模糊神经网络程序(to Matlab prepared by the pi-sigma FNN procedures)

Title: Noise and Vibration Analysis: Signal Analysis and Experimental Procedures Volume: Author(s): Anders Brandt Series: Periodical: Publisher: Wiley City: Year: 2011 Edition: 1 Language: English Pages: 445 ISBN: 0470746440, 9780470746448 (Noise and Vibration Analysis is a complete and practical guide that combines both signal processing and modal analysis theory with their practical application in noise and vibration analysis. It provides an invaluable, integrated guide for practicing engineers as well as a suitable introduction for students new to the topic of noise and vibration. Taking a practical learning approach, Brandt includes exercises that allow the content to be developed in an academic course framework or as supplementary material for private and further study.Addresses the theory and application of signal analysis procedures as they are applied in modern instruments and software for noise and vibration analysisFeatures numerous line diagrams and illustrationsAccompanied by a web site at www.wiley.com/go/brandt with numerous MATLAB tools and examples.Noise and Vibration Analysis provides an excellent resource for researchers and engineers automotive, aerospace, mechanical, or electronics industries who work)

用有限差分法求双脊金属加载矩形波导的基模及第一个高阶模的色散特性曲线( Finite difference method seeking double-ridged metal loaded rectangular waveguide fundamental mode and first higher order mode dispersion characteristic curve)

matlab函数的基本使用方法介绍，以便更好的学习matlab。(asic use matlab function introduced in order to better learning matlab.)

常见的滤波学习 中值滤波、均值滤波等 图像的解码(matlab )

反射式半导体光放大器的静态建模和动态建模(steady model and dynamic model of RSOA )

用于进行特征选择的方法，可以对数据进行降维，减少冗余。(For the method of feature selection, the data can be reduced and redundant.)