盖尔圆定理和最小描述长度准则相结合的信源数目估计方法研究

Research on Source Number Estimation based on Geschgorin Disk Estimator Theorem and Minimum Description Length Criterion

  • 摘要: 针对盲源分离算法应用中的源数估计问题,提出了一种结合盖尔圆定理(Geschgorin Disk Estimator, GDE)和最小描述长度准则(Minimum Description Length, MDL)的GDE-MDL源数估计方法。GDE-MDL方法集合了盖尔圆定理适用于空间色噪声的优点和MDL准则一致性估计的优点。该方法通过对观测信号协方差矩阵进行酉变换来抑制噪声,可以提高似然函数的灵敏度和信源数目的估计精度,更好的处理低信噪比和空间色噪声条件下的源数估计问题。仿真结果表明,GDE-MDL方法稳定性较好,适应性强,在白噪声和空间色噪声的情况下均可以较好的实现信源数目的估计。

     

    Abstract: This paper presents a method which combines Geschgorin Disk Estimator theorem (GDE) with Minimum Description Length criterion (MDL) for source number estimation in blind source separation. GDE-MDL method sets the advantages of GDE and MDL, which can accurately estimate the source number in color noise and improve the consistence of the source number estimation. This method based on the covariance matrix of the unitary transformation to suppress noise, can improve the sensitivity of plausibility function and have good applicability in low noise signal ratio and color noise. The simulation results show that the GDE-MDL method has good stability, and can achieve a better estimation of the number of sources in the case of white noise and color noise.

     

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