matlab2

QPSK modulation in matlab

经典的扩展卡尔曼滤波卡尔曼滤波程序，首先对非线性函数取一阶近似，生成近似的新型函数，然后进行卡尔曼滤波，通过一步状态和估协方差估计产生新息，然后生成状态预测(Classical extended Kalman filter, Kalman filter procedure, first take the first order approximation of nonlinear function to generate the new function approximation, and then proceed to the Kalman filter step state estimate covariance is estimated to generate new interest, and then generate the state prediction)

AK_model_and_Learning_by_doing_model matlab code

萤火虫算法（Firefly Algorithm）是一种启发式算法，灵感来自于萤火虫闪烁的行为。萤火虫的闪光，其主要目的是作为一个信号系统，以吸引其他的萤火虫。剑桥大学的Xin-She Yang（音译：杨新社）教授提出了萤火虫算法，其假设为[1]： 萤火虫不分性别，这样一个萤火虫将会吸引到所有其他的萤火虫 吸引力与它们的亮度成正比，对于任何两个萤火虫，不那么明亮的萤火虫被吸引，因此移动到更亮的一个，然而，亮度又随着其距离的增加而减少 如果没有比一个给定的萤火虫更亮的萤火虫，它会随机移动。 亮度应与目标函数联系起来。萤火虫算法是以自然为灵感的启发式优化算法(The Firefly Algorithm (are) Algorithm is a kind of heuristic Algorithm, inspired by the behavior of the fireflies flash. Fireflies flash, its main purpose is to as a signaling system, to attract other fireflies. The university of Cambridge, Xin- She Yang (transliteration: Yang Xinshe) professor firefly algorithm is proposed, its hypothesis in [1]. Fireflies regardless of gender, such a firefly will attract all the other fireflies Attractive proportional to their brightness, for any two fireflies, less bright fireflies are attracted, so moving to a brighter, however, brightness and reduce with the increase of the distance If there is no more than a given fireflies light of fireflies, it will move randomly. Brightness should be linked with the objective function. The firefly algorithm based on natural inspiration of heuristic optimization algorithm)

在matlab的环境下实现了自回归移动平均模型（arima）(Matlab environment in the realization of the auto-regressive moving average model (arima))

％％％ Demos for PUMA algorithms ％％％ We present four matlab demos for PUMA. demo1, demo2, demo3, and demo4 illustrate PUMA working with different parameters and with four different images. All you need to do is to run each of the demos. Please be sure that all the files are put on an accessible path for matlab. Notice that this code is intended for research purposes only. For further reference see "Phase Unwrapping via Graph Cuts, IEEE Transactions on Image Processing, 2007( Demos for PUMA algorithms We present four matlab demos for PUMA. Demo1, demo2, demo3, and demo4 illustrate PUMA working with different parameters and with four different images.All you need to do is to run each of the demos . Please be sure thatall the files are put on an accessible path for matlab.Notice that this code is intended for research purposes only.For further reference see )

说明：  非纹理的曲率驱动扩散的图像修复。参考文献：《Nontexture Inpainting by Curvature-Driven Diffusion》(Curvature-driven diffusion of non-texture image restoration. References: &quot CHAN Nontexture Inpainting by Curvature-Driven Diffusion&quot )

inverse dynamic of robot.nt to upload source code, you can

基于R-L模型的CT扫描和滤波反投影重建的程序实现(Based on CT scan and filter back projection reconstruction RL model program)

Arima模型选择差分项，并验证序列正确性(Arima model validates sequence correctness)