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Singular and Principal Subspace of Signal Information System by BROM Algorithm

机译:BROM算法的信号信息系统奇异主空间

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A novel algorithm for finding algebraic base of singular sub-space for signal information system is presented. It is based on Best Rank One Matrix (BROM) approximation for matrix representation of information system and on its subsequent matrix residua. Prom algebraic point of view BROM is a kind of power method for singular value problem. By attribute centering it can be used to determine principal subspace of signal information system and for this goal it is more accurate and faster than Oja's neural algorithm for PCA while preserving its adaptivity to signal change in time and space. The concept is illustrated by an exemplary application from image processing area: adaptive computing of image energy singular trajectory which could be used for image replicas detection.
机译:提出了一种寻找信号信息系统奇异子空间代数基的新算法。它基于信息系统矩阵表示的最佳秩一矩阵(BROM)近似及其后续矩阵残差。 Prom代数观点BROM是解决奇异值问题的一种幂方法。通过属性居中,它可以用于确定信号信息系统的主要子空间,并且为此目的,它比Oja的PCA神经算法更准确,更快,同时保留了它对时空信号变化的适应性。通过来自图像处理领域的示例性应用来说明该概念:可以用于图像副本检测的图像能量奇异轨迹的自适应计算。

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