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Improving the modeling of the noise part in the harmonic plus noise model of speech
2008 IEEE International Conference on Acoustics, Speech and Signal Processing, 2008Harmonic + noise model (HNM) is a hybrid model of speech with a harmonic component and a noise component. While the harmonic part describes efficiently the periodicities in speech signals (voiced parts), modeling of the noise part introduces artifacts primarily because of the specific time-domain characteristics of noise in voiced speech. In this paper,
Yannis Pantazis, Yannis Stylianou
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AUTOMATION OF A NATIONAL NOISE MODEL
Inter-Noise 2022, 2023The United Kingdom Department for Food and Rural Affairs (Defra) commissioned the design and build of an environmental noise modelling system (NMS). The NMS has been developed to support Defra in developing its environmental noise evidence base by preparing national road and railway noise models.
James Trow +5 more
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On transformation noise : properties and modeling
Journal of the Franklin Institute, 1993Abstract Some properties are studied of the class of discrete time transformation noise which is generally non-Gaussian and correlated and is generated by passing another noise process through an invertible memoryless nonlinearity. In general, any discrete time noise process can be considered as transformation noise.
AU, OC, THOMAS, JB
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2017
Chapter 3 introduces the Box-Jenkins AutoRegressive Integrated Moving Average (ARIMA) noise modeling strategy. The strategy begins with a test of the Normality assumption using a Kolomogov-Smirnov (KS) statistic. Non-Normal time series are transformed with a Box-Cox procedure is applied.
Richard McCleary +2 more
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Chapter 3 introduces the Box-Jenkins AutoRegressive Integrated Moving Average (ARIMA) noise modeling strategy. The strategy begins with a test of the Normality assumption using a Kolomogov-Smirnov (KS) statistic. Non-Normal time series are transformed with a Box-Cox procedure is applied.
Richard McCleary +2 more
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Geanakoplos and Sebenius model with noise [PDF]
International Journal of Game Theory, 1998 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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A stochastic model for the noise levels
The Journal of the Acoustical Society of America, 2009Accurate predictions of environmental noise levels are necessary to implement noise reduction strategies in urban areas. In this paper, a stochastic model is introduced to describe and predict the Lden, Lday, Levening, and Lnight levels. A Gaussian Ornstein–Uhlenbeck model is used to represent the dynamics of the noise levels, where the mean-reversion ...
A, Giménez, M, González
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On the Markov model of shot noise
Signal Processing, 1999zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Gregory Kotler +3 more
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Compact modeling of noise in CMOS
IEEE Custom Integrated Circuits Conference 2006, 2006The physical background of the thermal noise equations of the PSP MOSFET model [1] is presented. The PSP thermal noise model is shown to pass a number of proposed benchmark tests for MOSFET thermal noise. Without any fitting parameters, it is shown to predict with great accuracy a collection of experimental data on three modern CMOS technologies.
Andries J. Scholten +3 more
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The Journal of the Acoustical Society of America, 1963
A model of ambient sea noise is developed under the assumption of a surface distribution of noise sources. Volume absorption and the effects of refraction and reflection over long-range paths are included. The derived directional noise field is expressed as a function of vertical arrival angle, with the parameters being velocity profile, surface ...
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A model of ambient sea noise is developed under the assumption of a surface distribution of noise sources. Volume absorption and the effects of refraction and reflection over long-range paths are included. The derived directional noise field is expressed as a function of vertical arrival angle, with the parameters being velocity profile, surface ...
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Procedings of the British Machine Vision Conference 1990, 1990
Models of the sensor noise added in the picture capture process are important components of sensor models for vision systems. Most studies assume that the noise can be described by an additive, independent, identically distributed Gaussian model. This paper presents a test of this hypothesis.
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Models of the sensor noise added in the picture capture process are important components of sensor models for vision systems. Most studies assume that the noise can be described by an additive, independent, identically distributed Gaussian model. This paper presents a test of this hypothesis.
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