enkf-matlab-0.30.tar

Digital Bandpass Transmission(Digital Transmission)

协作通信系统的仿真 matlab仿真例程(Cooperative sensing communication system )

handwritten character recognition using back propagation neural network

FFT算法 在matlab中的实现 进行向量的计算(FFT algorith is relise in matlab and frequre amp phase)

mie理论的matlab源程序金属纳米粒子光散射的Mie 理论［附matlab源程序］(mie theory of metal nanoparticles matlab source of Mie light scattering theory [attached matlab source])

先对陀螺仪测量数据进行预处理，每隔100行抽取一行数据，以第7列数据为例，用ALLAN方差法分析出五项主要参数(First gyroscope measurement data preprocessing, extract a row of data every 100 rows, seven of data, for example, ALLAN variance analysis of the five main parameters)

Toet2016年在peer.J上发表的交替引导滤波论文的代码和图像，Alternating guided image filtering(Alternating guided image filtering)

说明：  This provides good overview for post-processing by Matlab

using terlis code to generate stbc

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)