Advances in Non-Linear Modeling for Speech ProcessingLinear and Dynamic System Model
Advances in Non-Linear Modeling for Speech Processing: Linear and Dynamic System Model
Holambe, Raghunath S.; Deshpande, Mangesh S.
2012-02-21 00:00:00
[In this chapter, we have discussed two types of widely used mathematical models, the linear model and the dynamic system model. The linear model and the dynamic system model (often formulated in a specific form called the state-space model) are two distinct types of mathematical structures, both with popular applications in many disciplines of engineering. These two types of the models have very different mathematical properties and computational structures. Instead of using a high-dimensional linear model to represent the temporal correlation structure of a signal, a low-dimensional dynamic system model can be used for efficient computations.]
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Advances in Non-Linear Modeling for Speech ProcessingLinear and Dynamic System Model
[In this chapter, we have discussed two types of widely used mathematical models, the linear model and the dynamic system model. The linear model and the dynamic system model (often formulated in a specific form called the state-space model) are two distinct types of mathematical structures, both with popular applications in many disciplines of engineering. These two types of the models have very different mathematical properties and computational structures. Instead of using a high-dimensional linear model to represent the temporal correlation structure of a signal, a low-dimensional dynamic system model can be used for efficient computations.]
Published: Feb 21, 2012
Keywords: Vocal Tract; Dynamic System Model; Linear Prediction Coefficient; Hide Markov Model State; Discrete Hide Markov Model
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