RoI

Hybrid kalman filter

用于无线通信系统中提高通信质量、减小误码率的有效措施的操作工具(Used in wireless communication systems to improve communication quality, effective measures to reduce the error rate)

LFMCW线性调频波仿真，MATLAB代码，信源部分仿真。(LFMCW linear frequency modulation wave simulation, MATLAB code, and source part of the simulation.)

该程序模拟了经典双稳系统随机共振中，噪声强度与系统做功的关系(The program simulates the classical stochastic resonance in bistable system, the relationship between noise intensity and the system to do work)

code NRZ nodeur NRZ sous matlab

CCISP考试指南与导读 CISSP STUDY NOTES FROM CISSP PREP GUIDE 1 DOMAIN 1 – SECURITY MANAGEMENT PRACTICES 2 DOMAIN 2 – ACCESS CONTROL SYSTEMS 7 DOMAIN 3 – TELECOM AND NETWORK SECURITY 13 DOMAIN 4 – CRYPTOGRAPHY 34 DOMAIN 5 – SECURITY ARCHITECTURE AND MODELS 46 DOMAIN 6 – OPERATIONS SECURITY 56 DOMAIN 7 – APPLICATIONS AND SYSTEM DEVELOPMENT 63 DOMAIN 8 – BUSINESS CONTINUITY AND DISASTER RECOVERY PLANNING 70 DOMAIN 9 – LAW, INVESTIGATION AND ETHICS 78 DOMAIN 10 – PHYSICAL SECURITY 87(CCISP test guidelines and guidance CISSP STUDY NOTES FROM CISSP PREP GUIDE 1DOMAIN 1- SECURITY MANAGEMENT PRACTICES 2DOMAIN 2- ACCESS CONTROL SYSTEMS 7DOMAIN 3- TELECOM AND NETWORK SECURITY 13DOMAIN 4- CRYPTOGRAPHY 34DOMAIN 5- SECURITY ARCHITECTURE AND MODELS 46DOMAIN 6- OPERATIONS SECURITY 56DOMAIN 7-- APPLICATIONS AND SYSTEM DEVELOPMENT 63DOMAIN 8- BUSINESS CONTINUITY AND DISASTER RECOVERY PLANNING 70DOMAIN 9- LAW, INVESTIGATION AND ETHICS 78DOMAIN 10- PHYSICAL SECURITY 87)

用matlab编辑音乐，模拟萧的声音演奏天空之城(Use matlab to edit music)

matlab线性系统分析,传递函数模型,质量－弹簧－阻尼系统,零极点增益模型（连续系统）(matlab linear system analysis, transfer function model, mass- spring- damper system, zero-pole-gain model (continuous system))

A useful source for car license plate recognition program to learn

基于MATLAB实现的说话人识别程序，分别用bp、pnn、som、rbf、lvq等算法，对语音文件进行训练和测试，效果不错。~..~ 下面说明一下bprengong程序： 数据分别用来训练和测试两部分。 具体程序分为两部分，第一部分为：计算识别模型 变量v是mfcc处理以后的矢量。因为数据可能长短不一，所以放在同一进行截取。p的每一行代表一个语音数据（共15个）。变量Pr为每一行的最大最小值。变量T为目标值。输出神经元个数为15。 在训练阶段，如果用于训练的输入训练样本的类别标号为i（即语音数据的标号），则训练时设第i个节点的期望输出设为1。其余节点期望输出均为0。 在识别时，当一个未知类别的样本作用到输入端时，考查各输出节点的输出，并将这个样本的类别判定为输出值最大的那个节点对应的类别。 (err)