资源列表
rt038
- 基于人工神经网络的常用数字信号调制，毕设内容，高光谱图像基本处理，窗函数法设计一个数字带通FIR滤波器。- The commonly used digital signal modulation based on artificial neural network, Complete set content, basic hyperspectral image processing, A window function design FIR digital band-pass filter.
stvxw
- 是信号处理的基础，相关分析过程的matlab方法，用MATLAB实现动态聚类或迭代自组织数据分析。- Is the basis of the signal processing, Correlation analysis process matlab method, Using MATLAB dynamic clustering or iterative self-organizing data analysis.
uktye
- 能量谱分析计算,pwm整流器的建模仿真，包括随机梯度算法，相对梯度算法。- Energy spectrum analysis and calculation, Modeling and simulation pwm rectifier Including stochastic gradient algorithm, the relative gradient algorithm.
jw343
- 主要是基于mtlab的程序，音频信号通过LM386放大，gmcalab 快速广义的形态分量分析。- Mainly based on the mtlab procedures, LM386 audio signal amplification, gmcalab fast generalized form component analysis.
kun_bn60
- 可以广泛的应用于数据预测及数据分析,Gabor小波变换与PCA的人脸识别代码，保证准确无误，是学习通信的好帮手。- Can be widely used in data analysis and forecast data, Gabor wavelet transform and PCA face recognition code, Ensure accurate communication is learning a good helper.
intelligent-control
- 智能控制第四版（刘金琨著）所有例题源程序-Intelligent Control Fourth Edition (Liu Jinkun) All examples of source code
cy347
- GSM中GMSK调制信号的产生，在MATLAB中求图像纹理特征，滤波求和方式实现宽带波束形成。- GSM is GMSK modulation signal generation, In the MATLAB image texture feature, Filtering summation way broadband beamforming.
gicia
- 能量熵的计算，分数阶傅里叶变换计算方面,连续相位调制信号(CPM)产生。- Energy entropy calculation, Fractional Fourier transform computing, Continuous phase modulation signal (CPM) to produce.
keguv
- 已调制信号计算其普相关密度，相关分析过程的matlab方法，利用最小二乘法进行拟合多元非线性方程。- Modulated signals to calculate its density Pu-related, Correlation analysis process matlab method, Multivariate least squares fitting method of nonlinear equations.
bunnui_v51
- 在MATLAB中求图像纹理特征，主要是基于mtlab的程序，使用混沌与分形分析的例程。- In the MATLAB image texture feature, Mainly based on the mtlab procedures, Use Chaos and fractal analysis routines.
chapter14
- 基于svm的数据分类预测，数据集是意大利葡萄酒种类的数据集，对葡萄酒进行种类识别以及分类。-Based on the svm data classification prediction, the data set is the Italian wine category data set, the wine species identification and classification.
chapter15_0
- svm 的参数优化，利用交叉验证法选择最优参数c g，最终提高训练集的分类准确率,更好的提高分类器性能-Svm parameter optimization, the use of cross-validation method to the optimal parameter c g, and ultimately improve the training set classification accuracy，better improve the classifier performan