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- 利用人工神经网络算法对人体心电信号进行特征提取并进行识别
sasdw.rar
- 现有数字信号自动调制识别方法大多只适用于无记忆信号，如PSK、ASK、FSK信号等。将有记忆 信号(MSK信号)和无记忆信号一起考虑，提出了一种改进的数字信号自动识别方法。该方法采用信号的瞬时统 计量作为特征参数，采用多层神经网络作为分类器。计算机仿真表明：当噪声采用高斯白噪声，并且信噪比大于 l5 dB时，识别率高于96％ ；当信噪比不低于l0 dB时，识别率不低于90％。,Existing digital signal automatic modulation recognition
pipeilvboqi
- 通过采用神经网络中的Clipping方法和MonteCarlo修改学习算法，对用于光学模式识别的纯相位二值化匹配滤波器进行了优化设计。计算机模拟结果表明，和传统的纯相位匹配滤波器的相关输出结果相比，其识别输出的信噪比和信号相关峰值得到了明显的提高，从而为今后的光学实现奠定了良好的基础。-Through the use of neural network methods and MonteCarlo modify Clipping learning algorithm for optical pa
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- 小波神经网络的信号调制识别研究小波神经网络的信号调制识别研究-Wavelet neural network identification of signal modulation wavelet neural network identification of signal modulation
Bee-algorithm5
- Bee algorithm Bee algorithm(1)信号处理、(2)人工智能与模式识别、(3)神经网络、(4)图像处理、(5)数据挖掘、-Bee algorithm3
xiaoboshenjingwangluo
- 提出了采用小波包的方法对供暖双吸式离心水泵轴承振动信号进行去噪和提取表征 相应轴承故障的频带能量 并采用 BP 神经网络进行训练和故障识别 通过 MATLAB 进行了仿真经试验验证该方法能够有效地识别出轴承故障-The wavelet package is adoptted to De-noise and extract band energy that represent bearing fault. and the BP neural network is adopting to t
1234-bp
- bp神经网络识别语音信号，是个很好的学习资料-BP neural network recognition of speech signals, is a very good learning materials
MFL
- 基于改进BP神经网络算法的管道缺陷漏磁信号识别-Identification of magnetic flux leakage signals of Pipeline Defects Based on improved BP neural network algorithm
rx466
- 包括压缩比、运行时间和计算复原图像的峰值信噪比,实现了对10个数字音的识别程序基于人工神经网络的常用数字信号调制。- Including compression ratio, image restoration computing uptime and peak signal to noise ratio, Realization of 10 digital audio recognition program The commonly used digital signal modulation
qi777
- 已调制信号计算其普相关密度，有小波分析的盲信号处理，BP神经网络用于函数拟合与模式识别。- Modulated signals to calculate its density Pu-related, There Wavelet Analysis Blind Signal Processing, BP neural network function fitting and pattern recognition.
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- 光纤陀螺输出误差的allan方差分析，BP神经网络用于函数拟合与模式识别，使用高阶累积量对MPSK信号进行调制识别。- allan FOG output error variance analysis, BP neural network function fitting and pattern recognition, Using high-order cumulants of MPSK signal modulation recognition.
2007
- 应用小区域方差对比，程序简单，在matlab环境中自动识别连通区域的大小,基于人工神经网络的常用数字信号调制。- Application of small area variance comparison, simple procedures, Automatic identification in the matlab environment the size of the connected area, The commonly used digital signal modulation
seqkd
- BP神经网络用于函数拟合与模式识别，Pisarenko谐波分解算法,给出接收信号眼图及系统仿真误码率。- BP neural network function fitting and pattern recognition, Pisarenko harmonic decomposition algorithm, The received signal is given eye and BER simulation systems.