WienerFilter_matlab

PUDN XIEXIE西南交通大学赵宏宇老师的教学课件(ORIGIN OF SEJTU.)

说明：  speech recognition using 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)

Matlab code for fiber bragg gratimg tmm

实现各种图的网络结构的实现方法，是学习传感器网络的很好的软件(Network structure to achieve a variety of graph realization method is good to learn a software sensor networks)

说明：  cma自适应恒模算法，由接受信号估计信道的自适应恒模算法(cma constant modulus adaptive algorithm, to receive signals from the adaptive channel estimate constant modulus algorithm)

模拟多径效应和多普勒频移，在不同时延下的仿真(multipath and doppler shift)

This is a journal that you need to build a AAC Compression

用于直齿轮进行疲劳设计的MATlab程序，敬请分享，并指导！(for the fatigue analysis of spur gear ,developed by matlab softwore,please share with all of you,and comunicate with each other )

MUSIC（多重信号提取）分析与仿真,从加有噪声的观测信号中分析提取出原信号(MUSIC (multiple signal extraction) analysis and simulation, plus a noise from the observation signal analysis to extract the original signal)