Results 11 to 20 of about 7,700,165 (256)
Differentiable Measures for Speech Spectral Modeling
IEEE Access, 2022 Autoregressive models for the envelope of speech power spectral densities (PSDs) are refined by the self-supervised spectral learning machine (S3LM) provided with differentiable spectral objective functions, including the Itakura-Saito divergence (ISD ...
Miguel Arjona Ramirez +3 more
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Frontiers in Astronomy and Space Sciences, 2017 Spectroscopic studies of active galactic nuclei (AGN) are powerful means of probing the physical properties of the ionized gas within them. In particular, near future observational facilities, such as the James Webb Space Telescope (JWST), will allow ...
Anna Feltre +9 more
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Resilience of the spectral standard model [PDF]
Journal of High Energy Physics, 2012 Abstract We show that the inconsistency between the spectral Standard Model and the experimental value of the Higgs mass is resolved by the presence of a real scalar field strongly coupled to the Higgs field. This scalar field was already present in the spectral model and we wrongly neglected it in our previous computations. It was
Chamseddine, Ali H., Connes, Alain
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Prediction of soil organic matter and clay contents by near-infrared spectroscopy - NIRS [PDF]
Ciência Rural, 2020 : Among the soil constituents, special attention is given to soil organic matter (SOM) and clay contents, since, among other aspects, they are key factors to nutrient retention and soil aggregates formation, which directly affect the crop production ...
Bruno Pedro Lazzaretti +5 more
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Fourier Spectral Methods for Nonlocal Models [PDF]
Journal of Peridynamics and Nonlocal Modeling, 2020 Efficient and accurate spectral solvers for nonlocal models in any spatial dimension are presented. The approach we pursue is based on the Fourier multipliers of nonlocal Laplace operators introduced in a previous work. It is demonstrated that the Fourier multipliers, and the eigenvalues in particular, can be computed accurately and efficiently.
Bacim Alali, Nathan Albin
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Hidden Markov models with spectral features for 2D shape recognition [PDF]
, 2001 We present a technique using Markov models with spectral features for recognizing 2D shapes. We analyze the properties of Fourier spectral features derived from closed contours of 2D shapes and use these features for 2D pattern recognition.
Cai, Jinhai, Liu, Zhi-Qiang
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Frontiers in Neuroscience, 2022 We review recent advances in using mathematical models of the relationship between the brain structure and function that capture features of brain dynamics. We argue the need for models that can jointly capture temporal, spatial, and spectral features of
Ashish Raj +2 more
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Spectral detection in the censored block model [PDF]
2015 IEEE International Symposium on Information Theory (ISIT), 2015 We consider the problem of partially recovering hidden binary variables from the observation of (few) censored edge weights, a problem with applications in community detection, correlation clustering and synchronization. We describe two spectral algorithms for this task based on the non-backtracking and the Bethe Hessian operators. These algorithms are
Saade, Alaa +3 more
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Singular-spectral climate models [PDF]
E3S Web of ConferencesIn this paper, the singular spectrum analysis method is used to construct data models for the Onega Lake basin: time series of air temperature, precipitation, and runoff of the Shuya, Suna, and Vodla rivers.
Belashev Boris
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A Spectral Model of Turnover Reduction [PDF]
Econometrics, 2015 We give a simple explicit formula for turnover reduction when a large number of alphas are traded on the same execution platform and trades are crossed internally. We model turnover reduction via alpha correlations. Then, for a large number of alphas, turnover reduction is related to the largest eigenvalue and the corresponding eigenvector of the alpha
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