用于神经磁源重建的标量和矢量最小方差波束形成器的渐近信噪比。
Asymptotic SNR of scalar and vector minimum-variance beamformers for neuromagnetic source reconstruction.
作者信息
Sekihara Kensuke, Nagarajan Srikantan S, Poeppel David, Marantz Alec
机构信息
Department of Electronic Systems and Engineering, Tokyo Metropolitan Institute of Technology, Tokyo 191-0065, Japan.
出版信息
IEEE Trans Biomed Eng. 2004 Oct;51(10):1726-34. doi: 10.1109/TBME.2004.827926.
To reconstruct neuromagnetic sources, the minimum-variance beamformer has been extended to incorporate the three-dimensional vector nature of the sources, and two types of extensions-the scalar- and vector-type extensions-have been proposed. This paper discusses the asymptotic signal-to-noise ratio (SNR) of the outputs of these two types of beamformers. We first show that these two types of beamformers give exactly the same output power and output SNR if the beamformer pointing direction is optimized. We then compare the output SNR of the beamformer with optimum direction to that of the conventional vector beamformer formulation where the beamformer pointing direction is not optimized. The comparison shows that the beamformer with optimum direction gives an output SNR superior to that of the conventional vector beamformer. Numerical examples validating the results of the analysis are presented.
为了重建神经磁源，最小方差波束形成器已得到扩展，以纳入源的三维矢量特性，并且已经提出了两种类型的扩展——标量型和矢量型扩展。本文讨论了这两种类型波束形成器输出的渐近信噪比（SNR）。我们首先表明，如果波束形成器的指向方向经过优化，那么这两种类型的波束形成器会给出完全相同的输出功率和输出SNR。然后，我们将具有最佳方向的波束形成器的输出SNR与传统矢量波束形成器公式（其中波束形成器的指向方向未优化）的输出SNR进行比较。比较结果表明，具有最佳方向的波束形成器的输出SNR优于传统矢量波束形成器。文中给出了验证分析结果的数值示例。
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