QuadrotorSimulator

用于图像的压缩，可以处理许多的图像问题，好可以节省很大的内存和空间(press)

卡尔曼滤波器、粒子滤波器、贝叶斯滤波器的资料及实现，很全的，对于基础学习和提高都有帮助。希望对大家有帮助。(Kalman filter, particle filters, Bayesian filters the information and the realization of very wide, and for basic learning and helpful. Hope to help.)

迭代思想的代码，网上搜寻的，希望对大家啊有帮助！(turbo code (Iterative Solutions))

Digital Signal Processing using Matlab

用七元线形天线阵（ULA） 已知：信号中心波长为2,天线阵元的间距为1米,快拍数为2000，空中有四个 源信号,假设它们的频率：0.015, 0.05, 0.02, 0.035 四个源信号的方向分别为：pi/4 pi/3 pi/6 3pi/4 求： 1）在不加入噪声的情况下,画出传统波束形成法、Bartlett波束 形成法、Capon波束形成法的空间谱图； 2）在加入高斯白噪声的情况下,假设信噪比为10dB，画出传统波束 形成法、Bartlett波束形成法、Capon波束形成法的空间谱图。(7-element linear antenna array (ULA) Known: the signal center wavelength is 2, the antenna element spacing of 1 m, the number of snapshots for 2000, the air there are four Source signal, assuming that their frequency: 0.015, 0.05, 0.02, 0.035 The direction of the four source signals: pi/4 pi/3 pi/6 3pi/4 Requirements: 1) not to join the noise, to draw the traditional beam-forming method, Bartlett, beam Formation method, Capon beamforming method of the space spectrum 2) by adding Gaussian white noise, assuming that the SNR is 10dB, to draw the traditional beam Formation method, Bartlett, beamforming, Capon beamforming method of the space spectrum.)

该文件是产生两组随即的高斯分布系列，均值为0，均方差为N/2(The document was then produced two series of Gaussian distribution, the mean of 0 and standard deviation of the N/2)

粒子群优化算法（PSO）是一种基于种群的随机优化技术，由Eberhart和Kennedy于1995年提出。粒子群算法模仿昆虫、兽群、鸟群和鱼群等的群集行为，这些群体按照一种合作的方式寻找食物，群体中的每个成员通过学习它自身的经验和其他成员的经验来不断改变其搜索模式。 (Particle swarm optimization algorithm (PSO) is a population based stochastic optimization technique, put forward by Eberhart and Kennedy in 1995. Particle swarm optimization (pso) algorithm on insects, herds, flocks and schools of fish swarm behavior, and these groups to find food in a cooperative way, each member of the group itself by learning experience and the experience of the other members to continuously change its search pattern.)

两个盲源分离程序 分别对应文章《Underdetermined Blind Source Separation using Sparse Representations》和《Underdetermined blind separation of delayed sound sources in the frequency domain》(Blind Source Separation )

it is useful for my research work

复杂网络中的适应度模型，BA模型的改进，采用指数分布(To adapt to the complexity of the network model, BA model of improvement, the use of exponential distribution)