datagen

说明：  本程序主要是对CSRZ-8DPSK进行调制，并仿真出时域图、相位图、相位差图以及频谱图。(The program mainly for CSRZ-8DPSK modulation and time domain simulation diagram, phase diagram, phase diagram and the frequency spectrum.)

A Comprehensive Comparison Study of Document Clustering for a Biomedical Digital Library MEDLINE(综合比较研究文档聚类的医学数字图书馆检索)(A Comprehensive Comparison Study of Docum ent Clustering for a Biomedical Digital Librar y MEDLINE (Integrated Document Clustering comparative study of medical digital library retrieval))

利用雷达搜索方程，分别分析功率孔径积与检测目标距离、孔径大小的关系，得出相应的结论。(Using radar search equation analysis of the relationship between the power aperture product testing target distance, aperture size, and draw the appropriate conclusions.)

说明：  病态矩阵HILBERT，正则化高斯消元法，cholesky分解法(Ill-conditioned matrix HILBERT, regularization of Gaussian elimination method, cholesky decomposition)

本代码主要是仿真了阵列信号的music算法的基本性能。如估计精度随信噪比的变化和天线孔径的变化。(This code is mainly the array signal simulation algorithm for the basic properties of music. If the SNR estimation accuracy with the changes and changes in the antenna aperture.)

《雷达信号分析》ppt,南京理工大学 朱晓华 教授 博士生导师 主讲 比较经典 希望对大家有帮助("Radar signal analysis" ppt, Nanjing University of Science PhD supervisor Professor Zhu Xiaohua more classic speakers we want to help)

matlab解决0/1线性规划问题NP难题，(matlab solve the 0/1 linear programming problem NP problem,)

用MATLAB 编写的 ADPCM 编解码器(MATLAB prepared ADPCM codec)

说明：  实现多尺度熵的算法 多尺度熵（Multiscale entropy, MSE）将样本熵扩展到多个时间尺度，以便在时间尺度不确定时提供额外的观察视角。样本熵的问题在于它没有很好地考虑到时间序列中可能存在的不同时间尺度。为了计算不同时间尺度下信号的复杂性，Costa等人（2002,2005）提出了多尺度熵。(MultiScale Entropy There has been considerable interest in quantifying the complexity of physiologic time series, such as heart rate. However, traditional algorithms indicate higher complexity for certain pathologic processes associated with random outputs than for healthy dynamics exhibiting long-range correlations. This paradox may be due to the fact that conventional algorithms fail to account for the multiple time scales inherent in healthy physiologic dynamics. We introduce a method to calculate multiscale entropy (MSE) for complex time series. We find that MSE robustly separates healthy and pathologic groups and consistently yields higher values for simulated long-range correlated noise compared to uncorrelated noise.)

UKF and sigma points