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Speech enhancement algorithms are used to remove background noise in a speech signal. In Bayesian short-time spectral amplitude (STSA) estimation for single-channel speech enhancement, the spectral components are traditionally assumed uncorrelated. However, this assumption is inexact since some correlation is present in practice. In this paper, we investigate a multidimensional Bayesian STSA estimator...
In this paper, the acceleration of a car under performance tests is estimated by using a Kalman filter. Here, the observation vector consists of the observation of both the velocity and the longitudinal acceleration of the car. This is the process vector and is the input of the filter. The output is the filtered estimate of the state vector, which consist of the velocity and longitudinal acceleration...
The Extended Kalman Filter (EKF) algorithm is easy to be affected by the initial state value and the pseudo linear equation based algorithm will result in biased solution. A new asymptotically unbiased location and tracking algorithm with bearings-only measurements by two stations is proposed to solve these problems. The proposed algorithm introduces the correlation matrix of the observation error...
Taking the factor analysis problem of tone color, this paper finds that a semantically inconsistent correlation may occur if conventional factor analysis is applied to the data rated by the semantic differential in order to construct the correlation matrix. This paper proposes a new association analysis between two variables not using the correlation, and constructs a new factor analysis on the new...
A novel approach for generating nonlinear signal model with accurate noise response is proposed and demonstrated, which is realized with a cascade of a linear noise and a nonlinear signal models. The noise model behaves as a 0 Ohm resistor with arbitrary noise response. The noise response is described by a correlation matrix calculated directly from measured noise data. The noise model can easily...
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