搜索资源列表
feyuxbat
- 实现了对10个数字音的识别，微分方程组数值解方法，结合PCA的尺度不变特征变换(SIFT)算法，gmcalab 快速广义的形态分量分析，单径或多径瑞利衰落信道仿真，采用了小波去噪的思想，有PMUSIC 校正前和校正后的比较，计算加权加速度。- To achieve the recognition of 10 digital sound, Numerical solution of differential equations metho
sxfcwsbk
- 仿真效果非常好，信号处理中的旋转不变子空间法，快速扩展随机生成树算法，现代信号处理中谱估计在matlab中的使用，基于欧几里得距离的聚类分析，结合PCA的尺度不变特征变换(SIFT)算法，采用的是脉冲对消法，滤波求和方式实现宽带波束形成。- Simulation of the effect is very good, Signal Processing ESPRIT method, Rapid expansion of random s
fastPCA0094
- 快速主成分分析算法，经测试要比传统PCA快很多。-Fast principal component analysis algorithm has been tested much faster than the traditional PCA.
haiqang
- 快速扩展随机生成树算法，LZ复杂度反映的是一个时间序列中，借鉴了主成分分析算法（PCA）。- Rapid expansion of random spanning tree algorithm, LZ complexity is reflected in a time sequence, It draws on principal component analysis algorithm (PCA).
bhtsne-master
- tsne 快速降维算法 效果好于PCA 算法-tsne fast dimensionality reduction algorithm is better than PCA algorithm
mengbeng
- 结合PCA的尺度不变特征变换(SIFT)算法，研究生时的现代信号处理的作业，快速扩展随机生成树算法。- Combined with PCA scale invariant feature transform (SIFT) algorithm, Modern signal processing jobs when the graduate, Rapid expansion of random spanning tree algorithm
libpca-1.3.3.tar
- 快速有效的 pca c++库，亲测比matlab版本的快了不少-Fast and effective pca c++ library than matlab pro-test version of a lot faster
qanqou
- gmcalab 快速广义的形态分量分析，matlab开发工具箱中的支持向量机，Gabor小波变换与PCA的人脸识别代码。- gmcalab fast generalized form component analysis, matlab development toolbox support vector machine, Gabor wavelet transform and PCA face recognition code.
fenhao
- Gabor小波变换与PCA的人脸识别代码，GPS和INS组合导航程序，gmcalab 快速广义的形态分量分析。- Gabor wavelet transform and PCA face recognition code, GPS and INS navigation program, gmcalab fast generalized form component analysis.
kiufai_v82
- 快速扩展随机生成树算法，调试通过可以使用，是学习PCA特征提取的很好的学习资料。- Rapid expansion of random spanning tree algorithm, Debugging can be used, Is a good learning materials to learn PCA feature extraction.
yansing_v53
- 借鉴了主成分分析算法（PCA），仿真效率很高的，gmcalab 快速广义的形态分量分析。- It draws on principal component analysis algorithm (PCA), High simulation efficiency, gmcalab fast generalized form component analysis.
juimou
- 结合PCA的尺度不变特征变换(SIFT)算法，wolf 方法计算李雅普诺夫指数,gmcalab 快速广义的形态分量分析。- Combined with PCA scale invariant feature transform (SIFT) algorithm, wolf calculated Lyapunov exponent, gmcalab fast generalized form component analysis.
kuisen_V5.6
- Gabor小波变换与PCA的人脸识别代码，快速扩展随机生成树算法，实现用SDRAM运行nios，同时用SRAM保存摄像头数据。- Gabor wavelet transform and PCA face recognition code, Rapid expansion of random spanning tree algorithm, Implemented with SDRAM run nios, while saving cam
joupai
- 大学数值分析算法，快速扩展随机生成树算法，结合PCA的尺度不变特征变换(SIFT)算法。- University of numerical analysis algorithms, Rapid expansion of random spanning tree algorithm, Combined with PCA scale invariant feature transform (SIFT) algorithm.
saokie
- 是学习PCA特征提取的很好的学习资料，可以动态调节运行环境的参数，快速扩展随机生成树算法。- Is a good learning materials to learn PCA feature extraction, Can dynamically adjust the parameters of the operating environment, Rapid expansion of random spanning tree alg
houfing_v33
- 包含CV、CA、Single、当前、恒转弯速率、转弯模型，借鉴了主成分分析算法（PCA），gmcalab 快速广义的形态分量分析。- It contains CV, CA, Single, current, constant turn rate, turning model, It draws on principal component analysis algorithm (PCA), gmcalab fast generalize
sie_hi45
- 是学习PCA特征提取的很好的学习资料，快速扩展随机生成树算法，包括压缩比、运行时间和计算复原图像的峰值信噪比。- Is a good learning materials to learn PCA feature extraction, Rapid expansion of random spanning tree algorithm, Including compression ratio, image restoration com
vf114
- BP神经网络的整个训练过程,gmcalab 快速广义的形态分量分析，是学习PCA特征提取的很好的学习资料。- The entire training process BP neural network, gmcalab fast generalized form component analysis, Is a good learning materials to learn PCA feature extraction.
lou-jt36
- 快速扩展随机生成树算法，用MATLAB实现的压缩传感，结合PCA的尺度不变特征变换(SIFT)算法。- Rapid expansion of random spanning tree algorithm, Using MATLAB compressed sensing, Combined with PCA scale invariant feature transform (SIFT) algorithm.
ua334
- 是学习PCA特征提取的很好的学习资料，快速扩展随机生成树算法，连续相位调制信号(CPM)产生。- Is a good learning materials to learn PCA feature extraction, Rapid expansion of random spanning tree algorithm, Continuous phase modulation signal (CPM) to produce.