GREY-AFSA

MATLAB 的一写小总结，传上来供大家方便。欢迎下载。(MATLAB Writing a small summary of the 1, Chuan-up for the convenience of everyone. Welcome to download.)

两种先进的数字图像混沌加密方法,用MATLAB实现.经过调试.(Two kinds of advanced chaotic encryption methods, and use MATLAB to achieve. After debugging.)

多波束形成的代码，其中也有一些自适应的波束形成代码(beam forming)

source code and research

LDPC编解码代码，使用matlab中的Mex文件，解码速度较快(LDPC Codec using mex file in Matlab)

基于蒙特卡洛方法的主动声纳信号检测性能分析.主动声纳信号检测性能的分析上,目前在计算机仿真中一般假定混响包络的统计特性符合瑞利分布模型。基于此模型,已经有了较完善的理论。然而,在现代高分辨声纳系统中,混响包络的统计特性并不符合瑞利分布模型。此时在接收机工作特性分析时存在大量繁琐的公式推导。因此该文采用蒙特卡洛(M onte Carlo)统计试验方法,实现对瑞利分布混响背景下的主动声纳信号检测性能分析。结合对接收机工作特性曲线的仿真,得出了检测概率的理论值和仿真结果的误差曲线。误差曲线表明,蒙特卡洛方法在主动声纳信号检测的性能评估中是可行的。 更多还原 (Active sonar signal detection performance analysis, computer simulation is generally assumed that the statistical properties of the reverberation envelope distribution model of Rayleigh active sonar signal detection performance analysis based on the Monte Carlo method. Based on this model, has been a better theory. However, in the modern high-resolution sonar system, the statistical characteristics of the reverberation envelope does not comply with the Rayleigh distribution model. At this point in the receiver operating characteristic analysis, there is a lot of tedious formula derivation. In this paper, using the Monte Carlo (M onte Carlo) statistical test methods, active sonar signal detection performance analysis reverberation background Rayleigh distribution. The receiver operating characteristic curve simulation obtained the error curve of the theoretical value and the simulation results of the detection probability. The error curve shows that the Monte Carlo method in the assessm)

当水下存在多个目标时，利用平均声强器检测已经不再有效，此时使用复平均声强器来确定多目标的方位。(When existing multi sources, average acoustic intensity does work. At this case, complex average acoustic intensity can obtain the direction of multi sources.)

Jain & Yu机遇区域的文本定位方法实现(Jain & Yu opportunities for regional implementation of text localization)

说明：  高斯过程在分类中的应用。本程序采用拉普拉斯逼近基于高斯过程的贝叶斯分类。(Gaussian process in the Classification. This procedure uses the Laplace approximation of Gaussian processes based on Bayesian classification.)

两种滤波反投影重建方法的比较Filter back projection ct image reconstruction(Filter back projection ct image reconstruction)