Kai-Sheng Song

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We propose a novel methodology for estimating the shape parameter of a generalized Gaussian distribution (GGD). This new method is based on a simple estimating equation derived from a convex shape equation. The estimating equation is completely independent of gamma and polygamma functions. Thus, no lookup table, interpolation, or additional subroutine to(More)
Many applications in real-time signal, image, and video processing require automatic algorithms for rapid characterizations of signals and images through fast estimation of their underlying statistical distributions. We present fast and globally convergent algorithms for estimating the three-parameter generalized gamma distribution (G Gamma D). The proposed(More)
Accurate estimation of the amplitude and frequency parameters of sinusoidal signals from noisy observations is an important problem in many signal processing applications. In this paper, the problem is investigated under the assumption of non-Gaussian noise in general and Laplace noise in particular. It is proven mathematically that the maximum likelihood(More)
Based on an asymptotic analysis of the contraction mapping (CM) method of Li and Kedem (IEEE Trans. Inform. Theory, vol. 39, pp. 989–998, 1993), a bandwidth shrinkage rule is proposed for fast and accurate estimation of the frequencies of multiple sinusoids from noisy measurements. The CM frequency estimates are defined as the fixed-points of a contractive(More)
PURPOSE This research provides public policy implications regarding organ resource allocation and increases public awareness of the current status of transplant use in various ethnic populations. PROCEDURES Healthcare Cost and Utilization Project (HCUP), National Inpatient Sample (NIS) data were used to obtain a yearly estimate of the number of organ(More)
This correspondence revisits the asymptotic normality question of the nonlinear least-squares estimator for sinusoidal parameter estimation and fills a gap in the literature by providing a complete proof of the asymptotic normality under the assumption of additive non-Gaussian white noise. The result shows that the nonlinear least-squares estimator is able(More)
Traditional methods of estimating the frequency of sinusoids from noisy data include the periodogram maximization and the nonlinear least squares. It is well-known that these methods lead to efficient frequency estimates whose asymptotic standard error is of order O(n−3/2). To actually compute the estimates, some sort of iterative search procedures must be(More)
Based on an asymptotic analysis of the contraction mapping (CM) method of Li and Kedem (IEEE Trans. Inform. Theory, vol. 39, pp. 989–998, 1993), a bandwidth shrinkage rule is proposed for fast and accurate estimation of the frequencies of multiple sinusoids from noisy measurements. The CM frequency estimates are defined as the fixed-points of a contractive(More)
Twenty years ago Kay (1984) proposed an iterative filtering algorithm (IFA) for jointly estimating the frequencies of multiple complex sinusoids from noisy observations. It is based on the fact that the noiseless signal is an autoregressive (AR) process, so the frequency estimation problem can be reformulated as the problem of estimating the AR(More)