Receiving-Antenna

This is Uncstned particle filter demo code.

本书从计算、绘图和编程3 个方面介绍MATLAB 的基础知识，可供对MATLAB 感兴趣的大学生、研究生和科研人员阅读和使用。(Book from the calculations, drawing and programming 3 introduces the basics of MATLAB, MATLAB available for interested students, graduate students and researchers to read and use.)

Shimmer 2r heart rate detection algorithm

说明：  SCMA及ML检测，对非正交多址接入学习很有帮助(SCMA and ML detection)

QPSK-BPSK-ASK-FSK and MSK Modulations that will help in modulation issues. It is experimental for a College Project and it may needs some corrections. Thx for understanding.

利用Matlab自带的SVD函数，对带地形的二维数据场进行SVD分析(That comes with Matlab SVD function, SVD analysis on the two-dimensional data field with topography)

聚类分析中的划分聚类算法的k-means算法（随机选取矩阵数据）(Partition clustering algorithm in clustering analysis of k- means algorithm (random matrix data))

功率谱估计 信号为两个正弦信号加高斯白噪声，各正弦信号的信噪比均为10dB，长度为N，信号频率分别为 和 ，初始相位 ，取 ， 取不同数值：0.3，0.25。 为采样频率。分别用Levinson递推法和Burg法进行功率谱估计，并分析改变数据长度、模型阶数对谱估计结果的影响。(Power spectrum estimation signal into two sinusoidal signals applied Gaussian white noise, the SNR of each sinusoidal signal are 10dB, a length of N, respectively, and the signal frequency, initial phase, take, take different values: 0.3,0.25. Is the sampling frequency. Levinson recursive method were used and Burg method for power spectrum estimation, and change the length of the data analysis, the impact on the estimation model order spectrum.)

一种改进的萤火虫算法解决动态0-1背包问题。经过测试，算法就有良好的性能。(Firefly Algorithm (FA), Genetic Algorithm (GA) and Differential Evolution (DE) have been widely used for static optimization problems, but the applications of those algorithms in dynamic environments are relatively lacking. In the present study, an effective FA introducing diversity with partial random restarts and with an adaptive move procedure is developed and proposed for solving dynamic multidimensional knapsack problems. To the best of our knowledge this paper constitutes the first study on the performance of FA on a dynamic combinatorial problem. In order to uate the performance of the proposed algorithm the same problem is also modeled and solved by GA, DE and original FA. Based on the computational results and convergence capabilities we concluded that improved FA is a very powerful algorithm for solving the multidimensional knapsack problems for both static and dynamic environments.)

Test the optimized implementation of comparison with single-character strings.