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img-mhrg
- 分类器设计的好坏对于图像识别效果有着重要影响. 本文基于黄等所提出的识别方法,定义了一类更 广泛的隶属函数,并借助于投影算子理论、子空间理论,对所提隶属函数的性质进行了深入的理论分析,证明了所提隶 属函数所具有的若干良好特性,-Classifier design is good or bad for the image recognition results have an important impact. Yellow, etc. Based on the proposed reco
attachments_2010_07_03
- Projection Approximation Subspace Tracking & An Extension of the PASTd Algorithm to Both Rank and Subspace Tracking
getPDF1
- In this paper, we investigate the timing and carrier frequency offset (CFO) synchronization problem in decode and forward cooperative systems operating over frequency selective channels. A training sequence which consists of one orthogonal fr
getPDF2
- In this paper, we investigate the timing and carrier frequency offset (CFO) synchronization problem in decode and forward cooperative systems operating over frequency selective channels. A training sequence which consists of one orthogonal fr
cpofdm
- 基于子空间的盲信道估计算法，用的是奇异值的分解Subspace-based blind channel estimation algorithm, using a singular value decomposition -Subspace-based blind channel estimation algorithm, using a singular value decomposition
TLS_ESPRIT
- 阵列信号处理中的旋转不变子空间法。 原创-Array signal processing in the rotation invariant subspace method. Original. . . . . . . . . . . .
EM.tar
- This package uses iterative EM and K-Subspaces methods to estimate multiple subspace structures with all dimensions given.
RANSAC-subspaces.tar
- This package consists of two implementations about using ransom sampling techniques to estimate multiple subspaces: RANSACarrangement: Sample subsets to estimate a union of subspaces together. RANSACsubspaces: Estimate one subspace at a time w
SubspaceLearningCodes(Matlab)forFaceRecognition.ra
- 人脸识别的子空间方法，包括LLE，ISOMAP和NPE等维数约减算法-Subspace method for face recognition, including LLE, ISOMAP and NPE dimensionality reduction algorithm such as
fisherface
- Eigenfaces: PCA tends to find a p-dimensional subspace whose basis vectors correspond to the maximum variance direction in the original image space (p N). We called the new subspace defined by basis vectors “face space”. First, all training
imm922[1]
- 这篇文献的名称是：Analysis and Segmentation of Face Images using Point Annotations and Linear Subspace Techniques。介绍的方法实现都是基于IMM人脸数据库的。-The name of this literature is: Analysis and Segmentation of Face Images using Point Annotations and Linear Subspace Tech
subspaceTracking
- 标准的子空间跟踪算法，配合卡尔曼滤波算法，可用于移动用户跟踪-past-d subspace tracking
spalgorithmpackage
- 子空间追踪算法（SP）程序包，包含示例程序，SP算法程序及附属程序-Subspace pursuit algorithm (SP) package includes sample programs, SP algorithm program and ancillary procedures
Adaptive-vibration-controlwith-tracking-filters.ra
- 针对频率周期振荡的振动系统讨论自适应控制问题,在频率跟踪的基础上对频率变化的振动响应进行控 制,给出相应的估计、滤波与控制方法。首先在子空间辨识原理的基础上,通过测量信号自相关序列的递推运算获得信号 频率 然后根据估计频率实时调整带通滤波器的中心频率,使其跟踪信号频率,实现信号分量的跟踪滤波 最后在LMS方 法的基础上构造对信号分量进行控制的自适应控制器。-The adaptive vibration control of systems excited by forces of p
chapter5
- Subspace Techniques with AlphaStable Distributions-The optimal ML techniques employed in Chapter are often regarded as exceedingly complex due to the high computational load of the multivariate nonlinear optimization problem involved with thes
sparse_wsf
- 使用加权子空间拟合（WSF）实现稀疏均匀圆阵DOA估计。优化过程用的是最陡下降法。-Using weighted subspace fitting (WSF) SPARSE DOA estimation with uniform circular arrays. Optimization process using a steepest descent method.
classical_music_1
- MUSIC方法是Schmidt 在 1979 年首先提出的,并于1986 年重新发表。该方法和 Roy 于1986 年提出的 Esprit方法都是早期经典的超分辨率 DOA 估计方法 即超瑞利限的方法 ,他们同属特征结构的子空间方法。-MUSIC method is Schmidt first proposed in 1979, and re-released in 1986. The method and Roy in 1986, Esprit proposed methods are ear
6
- 本文提出一种复杂条件下基于子空间梯度方向直方图跟踪的方法, 实验结果表明,该方法能够在光照变化、噪声干扰、模糊、目标姿态和尺度改变,以及部分遮挡等恶劣条件下实现准确跟踪,比传统的跟踪方法具有更高的跟踪精度和跟踪鲁棒性,能够满足地面侦察任务在多种复杂条件下对感兴趣目标进行准确跟踪的需求-In this paper, under the conditions of a complex gradient direction histogram based on subspace tracking me
zikonjiannihe
- 用于求解信号子空间与阵列流型的拟合问题，即信号子空间的拟合与噪声子空间的拟合。-Used to solve the signal subspace and array manifold type of fitting that the signal subspace fitting and subspace fitting.
asdaxsw
- subspace iteration for matrix eigenvalue solutions su bspace iteration for matrix eigenvalue solutions subspace iteration for matrix eigenvalue solutions-subspace iteration for matrix eigenvalue solutions subspace iteration for matrix eigenval