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  2. Signed graph - Wikipedia

    en.wikipedia.org/wiki/Signed_graph

    The term signed graph is applied occasionally to graphs in which each edge has a weight, w(e) = +1 or −1. These are not the same kind of signed graph; they are weighted graphs with a restricted weight set. The difference is that weights are added, not multiplied. The problems and methods are completely different.

  3. Spectral graph theory - Wikipedia

    en.wikipedia.org/wiki/Spectral_graph_theory

    The 1980 monograph Spectra of Graphs [16] by Cvetković, Doob, and Sachs summarised nearly all research to date in the area. In 1988 it was updated by the survey Recent Results in the Theory of Graph Spectra. [17] The 3rd edition of Spectra of Graphs (1995) contains a summary of the further recent contributions to the subject. [15]

  4. Log-spectral distance - Wikipedia

    en.wikipedia.org/wiki/Log-spectral_distance

    The log-spectral distance (LSD), also referred to as log-spectral distortion or root mean square log-spectral distance, is a distance measure between two spectra. [1] The log-spectral distance between spectra () and ^ is defined as p-norm:

  5. Spectral shape analysis - Wikipedia

    en.wikipedia.org/wiki/Spectral_shape_analysis

    Spectral shape analysis relies on the spectrum (eigenvalues and/or eigenfunctions) of the Laplace–Beltrami operator to compare and analyze geometric shapes. Since the spectrum of the Laplace–Beltrami operator is invariant under isometries, it is well suited for the analysis or retrieval of non-rigid shapes, i.e. bendable objects such as humans, animals, plants, etc.

  6. Spectrochemistry - Wikipedia

    en.wikipedia.org/wiki/Spectrochemistry

    Spectrochemistry is the application of spectroscopy in several fields of chemistry. It includes analysis of spectra in chemical terms, and use of spectra to derive the structure of chemical compounds, and also to qualitatively and quantitively analyze their presence in the sample.

  7. Spectral clustering - Wikipedia

    en.wikipedia.org/wiki/Spectral_clustering

    An example connected graph, with 6 vertices. Partitioning into two connected graphs. In multivariate statistics, spectral clustering techniques make use of the spectrum (eigenvalues) of the similarity matrix of the data to perform dimensionality reduction before clustering in fewer dimensions. The similarity matrix is provided as an input and ...

  8. Zendaya Says ‘I Had Such a Fear of Peeing or S—ting Myself ...

    www.aol.com/zendaya-says-had-fear-peeing...

    Zendaya revealed in a new interview with W Magazine that she suffered a heatstroke on the set of Denis Villeneuve’s “Dune: Part Two” because she stopped drinking water on the film’s very ...

  9. Spectrogram - Wikipedia

    en.wikipedia.org/wiki/Spectrogram

    Spectrograms of light may be created directly using an optical spectrometer over time.. Spectrograms may be created from a time-domain signal in one of two ways: approximated as a filterbank that results from a series of band-pass filters (this was the only way before the advent of modern digital signal processing), or calculated from the time signal using the Fourier transform.