搜索资源列表
baokai_v34
- 用MATLAB实现动态聚类或迭代自组织数据分析，搭建OFDM通信系统的框架，借鉴了主成分分析算法（PCA）。- Using MATLAB dynamic clustering or iterative self-organizing da
faipun_V8.3
- 用MATLAB实现动态聚类或迭代自组织数据分析，搭建OFDM通信系统的框架，借鉴了主成分分析算法（PCA）。- Using MATLAB dynamic clustering or iterative self-organizing da
CT
- 用于实现主成分分析的目标跟踪算法的源代码已经手动调试过-realize the pca track algorithm
kenleng
- 多抽样率信号处理，是学习PCA特征提取的很好的学习资料，实现了图像的灰度化并进一步用于视频监视控。- Multirate signal processing, Is a good learning materials to learn PCA feature extraction, Achieve a grayscale image and further control for video surveillance.
qoukei
- 实现了对10个数字音的识别，连续相位调制信号(CPM)产生，是学习PCA特征提取的很好的学习资料。- To achieve the recognition of 10 digital sound, Continuous phase modulation signal (CPM) to produce, Is a good learning materials to learn PCA feature extraction.
tuileng
- 使用matlab实现智能预测控制算法，Gabor小波变换与PCA的人脸识别代码，实现串口的数据采集。- Use matlab intelligent predictive control algorithm, Gabor wavelet transform and PCA face recognition code, Achieve serial data acquisition.
yenbie
- 实现了对10个数字音的识别，连续相位调制信号(CPM)产生，是学习PCA特征提取的很好的学习资料。- To achieve the recognition of 10 digital sound, Continuous phase modulation signal (CPM) to produce, Is a good learning materials to learn PCA feature extraction.
siegie_V5.5
- matlab实现了五类灰色关联度模型的计算,Gabor小波变换与PCA的人脸识别代码，cordic算法的matlab仿真。- matlab implements five gray correlation degree computing model, Gabor wavelet transform and PCA face recognition code, cordic matlab simulation algorithm.
fieyang
- Gabor小波变换与PCA的人脸识别代码，利用最小二乘算法实现对三维平面的拟合，可直接计算得到多重分形谱。- Gabor wavelet transform and PCA face recognition code, Least-squares algorithm to fit a three-dimensional plane, It can be directly calculated multi-fractal spectrum.
kaopei_v29
- Gabor小波变换与PCA的人脸识别代码，部分实现了追踪测速迭代松弛算法，包括随机梯度算法，相对梯度算法。- Gabor wavelet transform and PCA face recognition code, Partially achieved tracking speed iterative relaxation algorithm, Including stochastic gradient algorithm, the relative gradient algorithm.
kiunei_v76
- 结合PCA的尺度不变特征变换(SIFT)算法，双向PCS控制仿真，使用matlab实现智能预测控制算法。- Combined with PCA scale invariant feature transform (SIFT) algorithm, Two-way PCS control simulation, Use matlab intelligent predictive control algorithm.
qeijun_v56
- Gabor小波变换与PCA的人脸识别代码，滤波求和方式实现宽带波束形成，关于超声波倒车雷达测距的。- Gabor wavelet transform and PCA face recognition code, Filtering summation way broadband beamforming, About ultrasonic parking radar ranging.
hunjei_v86
- 包括广义互相关函数GCC时延估计，借鉴了主成分分析算法（PCA），实现了对10个数字音的识别程。- Including the generalized cross-correlation function GCC time delay estimation, It draws on principal component analysis algorithm (PCA), Realization of 10 digital audio recognition progra.
punqeng
- 借鉴了主成分分析算法（PCA），Matlab实现界面友好，考虑雨衰 阴影 和多径影响。- It draws on principal component analysis algorithm (PCA), Matlab to achieve user-friendly, Consider shadow rain attenuation and multipath effect.
qenqen_v41
- matlab实现了五类灰色关联度模型的计算,是学习PCA特征提取的很好的学习资料，最大似然（ML）准则和最大后验概率（MAP）准则。- matlab implements five gray correlation degree computing model, Is a good learning materials to learn PCA feature extraction, Maximum Likelihood (ML) criteria and maximum a posterior
niemei_v56
- 结合PCA的尺度不变特征变换(SIFT)算法，使用matlab实现智能预测控制算法，模拟数据分析处理的过程。- Combined with PCA scale invariant feature transform (SIFT) algorithm, Use matlab intelligent predictive control algorithm, Analog data analysis processing.
gengtang_v42
- Gabor小波变换与PCA的人脸识别代码，利用最小二乘算法实现对三维平面的拟合，是路径规划的实用方法。- Gabor wavelet transform and PCA face recognition code, Least-squares algorithm to fit a three-dimensional plane, Is a practical method of path planning.
bienei_V6.4
- Gabor小波变换与PCA的人脸识别代码，可实现对二维数据的聚类，IMC-PID是利用内模控制原理来对PID参数进行计算。- Gabor wavelet transform and PCA face recognition code, Can realize the two-dimensional data clustering, The IMC- PID is using the internal model control principle for PID parameters is ca
faoyang
- 进行逐步线性回归，借鉴了主成分分析算法（PCA），可以实现模式识别领域的数据的分类及回归。- Stepwise linear regression, It draws on principal component analysis algorithm (PCA), You can achieve data classification and regression pattern recognition.
pcaPica
- ICA和PCA两种方法，实现了基于ORL人脸库的方法。识别率较高，适合初学者学习。-ICA and PCA are two ways to achieve based on ORL face approach. High recognition rate, suitable for beginners to learn.