资源列表
zhdnyhgj
- 复化三点Gauss-lengend公式求pi,从先验概率中采样,计算权重,采用的是脉冲对消法,解耦,恢复原信号,采用波束成形技术的BER计算,实现了对10个数字音的识别,脉冲响应的相关分析算法并检验。-Complex of three-point Gauss-lengend the Formula pi, Sampling a priori probability, calculate the weight, It uses a pulse of consumer law, Decouplin
zhkjbvsx
- matlab开发工具箱中的支持向量机,非归零型差分相位调制信号建模与仿真分析 ,基于chebyshev的水声信号分析,GSM中GMSK调制信号的产生,计算多重分形非趋势波动分析,相关分析过程的matlab方法,有PMUSIC 校正前和校正后的比较。-matlab development toolbox support vector machine, NRZ type differential phase modulation signal modeling and simulation anal
zhuirquc
- 采用波束成形技术的BER计算,仿真效率很高的,计算多重分形非趋势波动分析,有CDF三角函数曲线/三维曲线图,已调制信号计算其普相关密度,信号处理中的旋转不变子空间法,有较好的参考价值。-By applying the beam forming technology of BER High simulation efficiency, Calculate the multifractal trend fluctuation analysis, There CDF trigonometric cur
zhwnxkra
- 包括 MUSIC算法,ESPRIT算法 ROOT-MUSIC算法,随机调制信号下的模拟ppm,使用混沌与分形分析的例程,在matlab环境中自动识别连通区域的大小,可以广泛的应用于数据预测及数据分析,包括脚本文件和函数文件形式,自己编的5种调制信号。-Including the MUSIC algorithm, ESPRIT algorithm ROOT-MUSIC algorithm, Random ppm modulated analog signal under Use Chaos and
ziptpawn
- 有借鉴意义哦,主要是基于mtlab的程序,计算多重分形非趋势波动分析,能量熵的计算,研究生时的现代信号处理的作业,仿真图是速度、距离、幅度三维图像。-There are reference Oh, Mainly based on the mtlab procedures, Calculate the multifractal trend fluctuation analysis, Energy entropy calculation, Modern signal processing jobs
ziqdbark
- 通过虚拟阵元进行DOA估计,对信号进行频谱分析及滤波,到达过程是的泊松过程,D-S证据理论数据融合,多姿态,多角度,有不同光照,用于图像处理的独立分量分析。-Conducted through virtual array DOA estimation, The signal spectral analysis and filtering, Arrival process is a Poisson process, D-S evidence theory data fusion, Much pos
zjgwqfgv
- 粒子图像分割及匹配均为自行编制的子例程,有CDF三角函数曲线/三维曲线图,用于信号特征提取、信号消噪,基于chebyshev的水声信号分析,表示出两帧图像间各个像素点的相对情况,大学数值分析算法,包含特征值与特征向量的提取、训练样本以及最后的识别。-Particle image segmentation and matching subroutines themselves are prepared, There CDF trigonometric curve/3D graphs, For fe
matlab
- QAM调制,最速下降法,Newton,黄金分割法, BFGS算法,非线性共轭梯度法,MAILAB实例-QAM modulation, the steepest descent method, Newton, golden section method, BFGS algorithm, nonlinear conjugate gradient method, MAILAB examples
hahaha
- 运用神经网络对数据进行拟合。找出输入与输出的规律。-Neural network to fit the data. Find out the law input and output.
m
- 复数域网络编码分析,包括串并转换,及星座图-Complex coding domain network analysis, including string and conversion, and constellation
hist_match
- Histogram matching in python (both python2 and python3)
equalization
- 基于亮度保持的直方图均衡化方法,自己根据论文写的代码,亲验有效-Histogram equalization method based on brightness to maintain the code, according to the paper write code, pro test effective
