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<<<<<<< HEAD

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}

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<<<<<<< HEAD
=======
  note = {Comment: 12 pages, 4 Figures},
>>>>>>> refs/remotes/origin/synced/master

}

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}

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}

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}

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}

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}

<<<<<<< HEAD
@article{Dasbach2021_757790,
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}

=======
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@book{Flury1988_,
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}

<<<<<<< HEAD
@article{GarciadelMolino2013_042824,
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}

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}

<<<<<<< HEAD
@article{Grun2009_1126,
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}

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@article{Guhr1998_189,
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  keywords = {Chaos,Disordered solids,Random matrix theory,Statistical many-body theory},

}

@article{Gutzen2018_90,
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  keywords = {reproducibility,simulation,Spiking Neural network,SpiNNaker,statistical analysis,Validation},

}

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}

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  pmid = {15861182},
  keywords = {Animal Genetics and Genomics,Behavioral Sciences,Biological Techniques,Biomedicine,general,Neurobiology,Neurosciences},

}

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}

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}

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}

@article{Koltchinskii2000_113,
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  publisher = {{International Statistical Institute (ISI) and Bernoulli Society for Mathematical Statistics and Probability}},
  issn = {1350-7265},
  doi = {10.2307/3318636},
  abstract = {Let \$H\textbackslash colon L\_\{2\}(S,\textbackslash scr\{I\},P)\textbackslash mapsto L\_\{2\}(S,\textbackslash scr\{I\},P)\$ be a compact integral operator with a symmetric kernel h. Let Xi, i{$\in$} N, be independent S-valued random variables with common probability law P. Consider the n \texttimes{} n matrix {\~H}n with entries n-1h(Xi,Xj), 1 {$\leq$} i, j {$\leq$} n (this is the matrix of an empirical version of the operator H with P replaced by the empirical measure Pn), and let Hn denote the modification of {\~H}n, obtained by deleting its diagonal. It is proved that the l2 distance between the ordered spectrum of Hn and the ordered spectrum of H tends to zero a.s. if and only if H is Hilbert-Schmidt. Rates of convergence and distributional limit theorems for the difference between the ordered spectra of the operators Hn (or {\~H}n) and H are also obtained under somewhat stronger conditions. These results apply in particular to the kernels of certain functions H = {$\varphi$}(L) of partial differential operators L (heat kernels, Green functions).},

}

@article{Krzanowski1979_703a,
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  author = {Krzanowski, W. J.},
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  number = {367},
  pages = {703--707},
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  doi = {10.1080/01621459.1979.10481674},
  abstract = {A method is given for comparing principal component analyses conducted on the same variables in two different groups of individuals, and an extension to the case of more than two groups is outlined. The technique leads to a latent root and vector problem, which has also arisen in the comparison of factor patterns in separate factor analyses. Emphasis in the present article is on the underlying geometry and interpretation of the results. An illustrative example is provided.},
  keywords = {Analytical rotation,Congruence coefficient,Latent roots and vectors,Principal component analysis},
  annotation = {\_eprint: https://www.tandfonline.com/doi/pdf/10.1080/01621459.1979.10481674},

}

@article{Krzanowski1990_81,
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  langid = {english},
  keywords = {Between-group analysis,Canonical variate analysis,Common principal component model,Eigenvalues and eigenvectors,Matusita distance between populations,Metric scaling,Principal component analysis}
}

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  doi = {10.1103/PhysRevE.94.050101},

}

<<<<<<< HEAD
@article{Kullback1951_79,
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  doi = {10.1214/aoms/1177729694},

}

=======
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}

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  doi = {10.1070/SM1967v001n04ABEH001994},
  langid = {english},

}

<<<<<<< HEAD
@article{Mochizuki2016_5736,
  title = {Similarity in {{Neuronal Firing Regimes}} across {{Mammalian Species}}},
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  doi = {10.1523/JNEUROSCI.0230-16.2016},
  langid = {english},

}

=======
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@article{Mongillo2018_1463,
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  copyright = {2018 The Author(s), under exclusive licence to Springer Nature America, Inc.},
  langid = {english},

}

<<<<<<< HEAD
@article{Muir2015_042808,
  title = {Eigenspectrum Bounds for Semirandom Matrices with Modular and Spatial Structure for Neural Networks},
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  publisher = {{American Physical Society}},
  doi = {10.1103/PhysRevE.91.042808},

}

=======
>>>>>>> refs/remotes/origin/synced/master
@article{Nakagawa2007_591a,
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  keywords = {Bonferroni correction,confidence interval,effect size,effect statistic,meta-analysis,null hypothesis significance testing,p value,power analysis,statistical significance},
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}

@misc{Nest3.1,
  title = {{{NEST}} 3.1},
  author = {Deepu, Rajalekshmi and Spreizer, Sebastian and Trensch, Guido and Terhorst, Dennis and Vennemo, Stine Brekke and Mitchell, Jessica and Linssen, Charl and M{\o}rk, H{\aa}kon and Morrison, Abigail and Eppler, Jochen Martin and Kamiji, Nilton Liuji and {de Schepper}, Robin and Kitayama, Itaru and Kurth, Anno and {Morales-Gregorio}, Aitor and Nagendra Babu, Pooja and Plesser, Hans Ekkehard},
  year = {2021},
  month = sep,
  doi = {10.5281/zenodo.5508805},
  howpublished = {Zenodo},

}

<<<<<<< HEAD
=======
@misc{Nest3.2,
  title = {{{NEST}} 3.2},
  author = {{de Schepper}, Robin and Eppler, Jochen Martin and Kurth, Anno and Nagendra Babu, Pooja and Deepu, Rajalekshmi and Spreizer, Sebastian and Trensch, Guido and Pronold, Jari and Vennemo, Stine Brekke and Graber, Steffen and {Morales-Gregorio}, Aitor and Linssen, Charl and Benelhedi, Mohamed Ayssar and M{\o}rk, H{\aa}kon and Morrison, Abigail and Terhorst, Dennis and Mitchell, Jessica and Diaz, Sandra and Kitayama, Itaru and Enan, Mahdi and Kamiji, Nilton Liuji and Plesser, Hans Ekkehard},
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  doi = {10.5281/zenodo.5886894},
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}

>>>>>>> refs/remotes/origin/synced/master
@article{Newman2003_167,
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}

@article{Pernice2011_e1002059,
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  doi = {10.1371/journal.pcbi.1002059},
  langid = {english},
  keywords = {Action potentials,Covariance,Eigenvalues,Network analysis,Network motifs,Neural networks,Neurons,Probability distribution},

}

@article{Rajan_5,
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  author = {Rajan, Kanaka},
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  langid = {english},

}

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}

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}

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}

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=======
@article{Szucs2017_,
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=======
>>>>>>> refs/remotes/origin/synced/master

}

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}