Results 221 to 230 of about 254,314 (265)

Comparative Evaluation of Machine Learning and Conventional Material Decomposition Algorithms for Spectral Chest Radiography Using a CdTe Photon-Counting Detector. [PDF]

Sensors (Basel)
Marupudi S, Ghammraoui B.
europepmc   +1 more source

Estimation of soil salt content in the oasis tillage layer based on hyperspectral transformation and model combination. [PDF]

PLoS One
Guo Y, Wang X, Li D, Li K, Zhang Q.
europepmc   +1 more source

Regularized regression in ultra-small chemometric datasets: A methodological case study using FTIR spectra of Schiff bases. [PDF]

PLoS One
Rashedi KA, Alshammari TS, Alshammari KM, Alanazi TA, Shabbir J, Mehmood T.   +5 more
europepmc   +1 more source

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SPEECH SPECTRAL SEGMENTATION FOR SPECTRAL ESTIMATION AND FORMANT MODELLING

Speech and Hearing, 2005
The evaluation of accurate speech spectral estimates is of importance in many areas such as formant extraction, speaker/speech recognition etc. This work describes an approach based on Dynamic Progamming for the optimal segmentation of speech spectra into Selective Linear Predictive (LP) segments to minimise the discrepancy between real and model ...
Harprit S. Chhatwal, Anthony G. Constantinides   +1 more
openaire   +1 more source

Generalised Linear Spectral Models

SSRN Electronic Journal, 2013
AbstractThis chapter considers a class of parametric spectrum estimators based on a generalized linear model for exponential random variables with power link. The power transformation of the spectrum of a stationary process can be expanded in a Fourier series, with the coefficients representing generalized autocovariances.
Proietti, Tommaso, LUATI, ALESSANDRA
openaire   +2 more sources

Spectral jitter modeling and estimation

Biomedical Signal Processing and Control, 2009
This paper suggests a new method for short-time jitter estimation based on a mathematical model that describes the coupling of two periodical phenomena. Specifically, jitter is modeled as the movement of one of the two periodic phenomena with respect to the other. The proposed method measures this movement indirectly by taking into account the spectral
Miltiadis Vasilakis, Yannis Stylianou
openaire   +1 more source

The Spectral Method for General Mixture Models

SIAM Journal on Computing, 2005
We present an algorithm for learning a mixture of distributions based on spectral projection. We prove a general property of spectral projection for arbitrary mixtures and show that the resulting algorithm is efficient when the components of the mixture are logconcave distributions in $\Re^{n}$ whose means are separated.
Ravindran Kannan, Hadi Salmasian, Santosh S. Vempala   +2 more
openaire   +1 more source