phase_shifted_sampled

自己编写的改进ELMAN网络辨识程序.非常实用(I have written procedures to improve the ELMAN network identification. Very useful)

带有白噪声的周期信号和噪声信号的自相关，数字信号处理的经典算法。(White noise with a periodic signal and noise auto-correlation signal, digital signal processing algorithm for the classic.)

关于MATLAB线性规划的程序,给大家分享一下,希望大家多多指导.(on MATLAB linear planning process, to share with you, I hope Members can guide.)

nickelcadmium used in battery for inverter simulation

复化梯形积分和抛物线积分的源代码，可以直接加以应用(Re-integration of trapezoidal and parabolic points of the source code, can be applied directly)

很简单的交错网格有限差分正演程序，程序通俗易懂，非常适合初学者学习(Staggered grid finite difference)

基于Hilbert包络解调及倒谱分析法，在LabVIEW平台开发的齿轮箱故障诊断程序(Based on Hilbert envelope demodulation and cepstrum analysis, the gearbox fault diagnosis program developed on the LabVIEW platform)

paper based on pca and image fusion

This m-file generate wind speed using ARMA model.

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)