资源列表
kfwork
- 系统方程维数为10,卡尔曼滤波以及根据轨迹发生器生成的理想轨迹数据计算载体的参数-System Fang Chengwei number of 10, Kalman filtering, and based on the ideal trajectory generator generates a parameter trajectory data carrier
kalman400
- 基于传统思路的卡尔曼滤波参考程序，精度高，易于实现-Kalman filtering based on traditional ideas reference program, high precision, easy to implement
danxiangfangbonibian
- 单相方波逆变器的matlab仿真，可以用来理解其原理与结构以及控制方式-Single-phase square wave inverter matlab simulation can be used to understand the principle and the structure and the control mode
generateQ
- what i present there is part of the source code to solve problems with metaheuristics like tabu search, simulated annealing,genetic algorithms, etc
pujiangaijin
- 程序主要是在原有谱减算法的基础上通过调整改进增益的系数a，b来实现谱减的改进，改进的谱减法实现了很好的语音降噪效果。-In the original program is mainly based on spectral subtraction algorithm improved by adjusting the gain of the coefficients a, b to achieve improved spectral subtraction, improved spectral s
celiangSNR
- 程序主要是通过读入纯净的语音信号和对纯净语音信号加噪后的混合信号来实现测量加噪后语音信号的信噪比。测量准确度较高。-Read into the program mainly through pure voice signal and noise on the clean speech signal plus the mixed signal to achieve measurements with noise after the speech signal to noise ratio. Mea
tianjiazaoshegn
- 程序是对输入的语音信号添加已知信噪比的噪声，输入是纯净的语音信号和信噪比，输出是加噪后的语音信号。后半部分是验证前面所加信噪比是否正确的程序-Procedure is to add the input speech signal noise ratio of the noise is known, the input speech signal and pure noise ratio, after output speech signal plus noise. Latter is to ve
pujianandvad
- 程序主要是实现强噪音环境下的语音端点检测，首先通过谱减法对原始语音进行去噪，接着采用端点检测算法实现强噪音环境下的语音端点检测。-Program is to achieve strong noise environment speech endpoint detection, first by spectral subtraction on the original speech denoising, endpoint detection algorithm then uses strong n
SVMTool
- 对于学习支持向量机运用matlab编程很有用哦-For learning support vector machines using matlab programming useful oh
003
- 典型二阶系统的模糊控制与传统PID控制的性能比较-Fuzzy control algorithm instance
bpsj1
- 典型系统BP神经网络与传统PID控制性能的比较-Typical BP neural network and the traditional PID control performance comparison
bpsj2
- 典型系统BP神经网络与传统PID控制性能的比较-例子2-Typical BP neural network and the traditional PID control performance comparison