论文标题
白色噪声光谱图和高斯全部功能的本地最大值
Local maxima of white noise spectrograms and Gaussian Entire Functions
论文作者
论文摘要
We confirm Flandrin's prediction for the expected average of local maxima of spectrograms of complex white noise with Gaussian windows (Gaussian spectrograms or, equivalently, modulus of weighted Gaussian Entire Functions), a consequence of the conjectured double honeycomb mean model for the network of zeros and local maxima, where the area of local maxima centered hexagons is three times larger than the area of zero centered hexagons.更确切地说,我们表明的是,高斯光谱图归一化,因此其预期的零密度为1,预期密度为5/3临界点,其中1/3是局部最大值和4/3个鞍点,并计算频谱图的训练值(高度)的分布。这是通过首先根据高斯整个功能(GEF)编写频谱图来完成的。在Fock空间的翻译不变衍生物中考虑了极值(在这种情况下,与复杂差异几何形状的Chern连接相吻合)。我们还观察到,GEF的临界点恰好是高斯随机函数的零,在第一个较高的Landau级别中。我们讨论这些高斯随机函数的自然扩展:高斯韦尔 - 海森贝格函数和高斯双输入功能。该论文还包含有关白噪声谱图,几个发展之间联系的理论和应用的最新结果的书目回顾,并且部分旨在作为对该主题的行人介绍。
We confirm Flandrin's prediction for the expected average of local maxima of spectrograms of complex white noise with Gaussian windows (Gaussian spectrograms or, equivalently, modulus of weighted Gaussian Entire Functions), a consequence of the conjectured double honeycomb mean model for the network of zeros and local maxima, where the area of local maxima centered hexagons is three times larger than the area of zero centered hexagons. More precisely, we show that Gaussian spectrograms, normalized such that their expected density of zeros is 1, have an expected density of 5/3 critical points, among those 1/3 are local maxima, and 4/3 saddle points, and compute the distributions of ordinate values (heights) for spectrogram local extrema. This is done by first writing the spectrograms in terms of Gaussian Entire Functions (GEFs). The extrema are considered under the translation invariant derivative of the Fock space (which in this case coincides with the Chern connection from complex differential geometry). We also observe that the critical points of a GEF are precisely the zeros of a Gaussian random function in the first higher Landau level. We discuss natural extensions of these Gaussian random functions: Gaussian Weyl-Heisenberg functions and Gaussian bi-entire functions. The paper also contains a bibliographic review of recent results on the theory and applications of white noise spectrograms, connections between several developments, and is partially intended as a pedestrian introduction to the topic.