On the Generalization of the Random Projection Method for Problems of the Recovery of Object Signal Described by Models of Convolution Type

O. G. Revunova, A.V. Tyshcuk, О.О. Desiateryk
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引用次数: 1

Abstract

Introduction. In technical systems, there is a common situation when transformation input-output is described by the integral equation of convolution type. This situation accurses if the object signal is recovered by the results of remote measurements. For example, in spectrometric tasks, for an image deblurring, etc. Matrices of the discrete representation for the output signal and the kernel of convolution are known. We need to find a matrix of the discrete representation of a signal of the object. The well known approach for solving this problem includes the next steps. First, the kernel matrix has to be represented as the Kroneker product. Second, the input-output transformation has to be presented with the usage of Kroneker product matrices. Third, the matrix of the discrete representation of the object has to be found. The object signal matrix estimation obtained with the help of pseudo inverting of Kroneker decomposition matrices is unstable. The instability of the object signal estimation in the case of usage of Kroneker decomposition matrices is caused by their discrete ill posed matrix properties (condition number is big and the series of the singular numbers smoothly decrease to zero). To find solutions of discrete ill-posed problems we developed methods based on the random projection and the random projection with an averaging by the random matrices. These methods provide a stable solutions with a small computational complexity. We consider the problem of object signals recovering in the systems where an input-output transformation is described by the integral equation of a convolution. To find a solution for these problems we need to build a generalization for two-dimensional signals case of the random projection method. Purpose. To develop a stable method of the recovery of object signal for the case in which an input-output transformation is described by the integral equation of a convolution. Results and conclusions. We developed the method of a stable recovery of object signal for the case in which an input-output transformation is described by the integral equation of a convolution. The stable estimation of the object signal is provided by Kroneker decomposition of the kernel matrix of convolution, computation of random projections for Kroneker factorization matrices, and a selection of the optimal dimension of a projector matrix. The method is illustrated by its application in technical problems.
关于卷积型模型描述的目标信号恢复问题的随机投影方法的推广
介绍在技术系统中,用卷积型积分方程描述变换输入输出是一种常见的情况。如果通过远程测量的结果恢复物体信号,则这种情况会恶化。例如,在光谱测量任务中,对于图像去模糊等。输出信号的离散表示的矩阵和卷积的核是已知的。我们需要找到对象信号的离散表示矩阵。解决这个问题的众所周知的方法包括以下步骤。首先,核矩阵必须表示为Kroneker乘积。其次,输入输出变换必须使用Kroneker乘积矩阵来表示。第三,必须找到对象的离散表示的矩阵。利用Kroneker分解矩阵的伪逆得到的目标信号矩阵估计是不稳定的。在使用Kroneker分解矩阵的情况下,目标信号估计的不稳定性是由它们的离散不适定矩阵性质引起的(条件数很大,奇异数序列平滑地减少到零)。为了找到离散不适定问题的解,我们开发了基于随机投影和通过随机矩阵求平均的随机投影的方法。这些方法提供了计算复杂度较小的稳定解。我们考虑了在输入输出变换由卷积的积分方程描述的系统中目标信号的恢复问题。为了找到这些问题的解决方案,我们需要对随机投影方法的二维信号情况进行推广。意图针对输入输出变换由卷积的积分方程描述的情况,开发了一种稳定的目标信号恢复方法。结果和结论。对于输入输出变换由卷积的积分方程描述的情况,我们发展了目标信号的稳定恢复方法。目标信号的稳定估计是通过卷积的核矩阵的Kroneker分解、Kroneker因子分解矩阵的随机投影的计算以及投影矩阵的最优维数的选择来提供的。通过在技术问题中的应用说明了该方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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