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基于子空间算法的ofdm系统半盲估计,希望对信道估计的同仁有帮助!-subspace algorithm based on the semi-blind system ofdm estimate, and I hope to channel estimation colleagues help!
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The channel estimation algorithm is based on a subspace approach. The method works only for identifiable STBCs (excluding >=1-rate STBCs). See publication [1] for more detail about the algorithm and the identifiability conditions. The zip file con
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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
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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
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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
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基于子空间的波束形成算法,主要利用信号子空间投影的原理-Subspace-based beamforming algorithm, the main use of the principle of the signal subspace
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MUSIC算法是一种基于矩阵特征空间分解的方法。从几何角度讲,信号处理的观测空间可以分解为信号子空间和噪声子空间,显然这两个空间是正交的。信号子空间由阵列接收到的数据协方差矩阵中与信号对应的特征向量组成,噪声子空间则由协方差矩阵中所有最小特征值(噪声方差)对应的特征向量组成-MUSIC algorithm is a feature space based on matrix decomposition method. From the geometric point of view, the o
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MIMO雷达模型下一种子空间谱估计方法,采用过估计的方法,以避免信源数估计的问题,直接对数据协方差矩阵进行变换,从而构造了信号子空间投影矩阵和噪声子空间投影矩阵,不需要像经典的MUSIC一样对其进行特征分解,完全避开了在一般非理想情况下MUSIC算法必须面对的识别小特征值与大特征值的麻烦,降低了复杂度,而且该方法不受快拍数的影响,在相干源情况下也能准确的估计目标的入射角,不会出现伪峰。-A subspace based DOA (Direction-Of-Arrival) estimation
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基于类别相关近邻子空间的最大似然稀疏表示鲁棒图像识别算法-Category neighboring subspace-based maximum likelihood sparse representation robust image recognition algorithm
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Signal subspace identification is a crucial first step in many hyperspectral processing algorithms such as target detection, change detection, classification, and unmixing. The identification of this subspace enables a correct dimensionality reductio
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The shuffled complex evolution with principal components analysis–University of California at Irvine (SP-UCI) method is a global optimization algorithm designed for high-dimensional and complex problems. It is based on the Shuffled Complex Evolution
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基于子空间的MUSIC算法,求到达角、离开角-Subspace-based MUSIC algorithm, and angle of arrival, left corner
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子空间法计算DOA AOA,ESPRIT旋转不变法程序-Subspace method DOA AOA, ESPRIT rotation invariant method program
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MUSIC算法[1]是一种基于矩阵特征空间分解的方法。从几何角度讲,信号处理的观测空间可以分解为信号子空间和噪声子空间,显然这两个空间是正交的。信号子空间由阵列接收到的数据协方差矩阵中与信号对应的特征向量组成,噪声子空间则由协方差矩阵中所有最小特征值(噪声方差)对应的特征向量组成。-MUSIC algorithm [1] is a feature space based on matrix decomposition method. From the geometric point of vie
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MUSIC算法[1]是一种基于矩阵特征空间分解的方法。从几何角度讲,信号处理的观测空间可以分解为信号子空间和噪声子空间,显然这两个空间是正交的。信号子空间由阵列接收到的数据协方差矩阵中与信号对应的特征向量组成,噪声子空间则由协方差矩阵中所有最小特征值(噪声方差)对应的特征向量组成。-MUSIC algorithm [1] is a feature space based on matrix decomposition method. From the geometric point of vie
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MUSIC算法是一种基于矩阵特征空间分解的方法。从几何角度讲,信号处理的观测空间可以分解为信号子空间和噪声子空间,显然这两个空间是正交的。信号子空间由阵列接收到的数据协方差矩阵中与信号对应的特征向量组成,噪声子空间则由协方差矩阵中所有最小特征值(噪声方差)对应的特征向量组成。MUSIC算法就是利用这两个互补空间之间的正交特性来估计空间信号的方位。噪声子空间的所有向量被用来构造谱,所有空间方位谱中的峰值位置对应信号的来波方位。MUSIC算法大大提高了测向分辨率,同时适应于任意形状的天线阵列,但是原
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相关分析过程的matlab方法,bBMIalx参数部分实现了追踪测速迭代松弛算法,数学方法是部分子空间法,matlab开发工具箱中的支持向量机,ytgQAKV条件具有丰富的参数选项,基于matlab GUI界面设计。- Correlation analysis process matlab method, bBMIalx parameter Partially achieved tracking speed iterative relaxation algorithm, Mathematics
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基于matlab GUI界面设计,VTjXHEB参数双向PCS控制仿真,部分实现了追踪测速迭代松弛算法,可以动态调节运行环境的参数,jFkAiBo条件本程序的性能已经达到较高水平,数学方法是部分子空间法。- Based on matlab GUI interface design, VTjXHEB parameter Two-way PCS control simulation, Partially achieved tracking speed iterative relaxation al
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数学方法是部分子空间法,基于互功率谱的时延估计,在matlab环境中自动识别连通区域的大小,是本科毕设的题目,阐述了负荷预测的应用研究,大学数值分析算法,独立成分分析算法降低原始数据噪声。- Mathematics is part of the subspace, Based on the time delay estimation of power spectrum, Automatic identification in the matlab environment the size of
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文件夹包括:经典MUSIC算法、基于波束空间的MUSIC算法、Root-Music算法、前向平滑MUSIC算法、后向平滑MUSIC算法、双向平滑MUSIC算法、奇异值算法、线性预测算法及旋转不变子空间算法等,是学习空间谱估计的很好例程(Folders include: classical MUSIC algorithm, beamspace-based MUSIC algorithm, Root-Music algorithm, forward smoothing MUSIC algorithm
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