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Nonorthogonal Joint Diagonalization Algorithm Based on Trigonometric Parameterization

机译:基于三角参数化的非正交联合对角化算法

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摘要

The joint diagonalization technique is an important type of method for blind source separation. In this paper, a new approach is presented to joint diagonalization for a set of symmetric matrices with a general (and not necessarily orthogonal) matrix. The approach performs joint diagonalization via a series of symmetric eigen decompositions, including merits of simplicity, effectiveness, and computational efficiency. Simulation results demonstrate the potential improvement of the performance in the context of blind source separation.
机译:联合对角化技术是盲源分离的一种重要方法。在本文中,提出了一种新的方法来对具有一般(不一定是正交)矩阵的对称矩阵进行联合对角化。该方法通过一系列对称本征分解来执行联合对角化,包括简单性,有效性和计算效率的优点。仿真结果证明了在盲源分离的情况下性能的潜在提高。

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