Results 21 to 30 of about 561,044 (162)
Stabilised weighted linear prediction
Speech Communication, 2009 Weighted linear prediction (WLP) is a method to compute all-pole models of speech by applying temporal weighting of the square of the residual signal. By using short-time energy (STE) as a weighting function, this algorithm was originally proposed as an improved linear predictive (LP) method based on emphasising those samples that fit the underlying ...
Magi, Carlo +3 more
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Audio Signal Processing Using Fractional Linear Prediction
Mathematics, 2019 Fractional linear prediction (FLP), as a generalization of conventional linear prediction (LP), was recently successfully applied in different fields of research and engineering, such as biomedical signal processing, speech modeling and image processing.
Tomas Skovranek, Vladimir Despotovic
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IFAC Proceedings Volumes, 1991 Abstract In this contribution, an approach to nonlinear predictive control is discussed. The philosophy involves the use of an on-line optimisation algorithm to determine the future inputs that will minimise the deviations between desired and predicted outputs. Control, however, is implemented in a receding horizon fashion.
MJ. Willis +3 more
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Re-estimation of Linear Predictive Parameters in Sparse Linear Prediction [PDF]
2009 Conference Record of the Forty-Third Asilomar Conference on Signals, Systems and Computers, 2009 In this work, we propose a novel scheme to re-estimate the linear predictive parameters in sparse speech coding. The idea is to estimate the optimal truncated impulse response that creates the given sparse coded residual without distortion. An all-pole approximation of this impulse response is then found using a least square approximation. The all-pole
Giacobello, Daniele +4 more
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Source enhanced linear prediction of speech incorporating simultaneously masked spectral weighting
Journal of Telecommunications and Information Technology, 2001 Linear prediction is the cornerstone of most modern speech compression algorithms. This paper proposes modifying the calculation of the linear predictor coefficients to incorporate a~weighting function based on the simultaneous masking property of the ...
Jason Lukasiak , Ian S. Burnett
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Audio Steganalysis Estimation with the Goertzel Algorithm
Applied SciencesAudio steganalysis has been little explored due to its complexity and randomness, which complicate the analysis. Audio files generate marks in the frequency domain; these marks are known as fingerprints and make the files unique.
Blanca E. Carvajal-Gámez +4 more
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Prediction of Black Soldier Fly Larva Sales and Production Using Linear Regression Method
Paradigma, 2023 The waste problem is a problem that plagues the world. Various programs and methods have been carried out in processing waste. Until now, Bali has become the area with the most waste production in Indonesia, where every day the waste produced reaches 4 ...
I Made Arya Budhi Saputra +6 more
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Informatics in Medicine Unlocked, 2021 Generally, health care costs from chronic diseases have positive skew and this gives problems on using traditional statistical models. Machine learning is a conventional method producing accurate prediction with large sample size.
Wichayaporn Thongpeth, M.N.S. +4 more
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Linear and non-linear bias: predictions versus measurements [PDF]
Monthly Notices of the Royal Astronomical Society, 2016 We study the linear and non-linear bias parameters which determine the mapping between the distributions of galaxies and the full matter density fields, comparing different measurements and predictions. Associating galaxies with dark matter haloes in the MICE Grand Challenge N-body simulation we directly measure the bias parameters by comparing the ...
Hoffmann, Kai +2 more
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Linear Reduced-Order Model Predictive Control
IEEE Transactions on Automatic Control, 2022 Model predictive controllers use dynamics models to solve constrained optimal control problems. However, computational requirements for real-time control have limited their use to systems with low-dimensional models. Nevertheless, high-dimensional models arise in many settings, for example discretization methods for generating finite-dimensional ...
Joseph Lorenzetti +3 more
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