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The generalized Gaussian distribution (GGD) provides a flexible and suitable tool for data modeling and simulation, however the characterization of the complex-valued GGD, in particular generation of samples from a complex GGD have not been well defined in the literature. In this study, we provide a thorough presentation of the complex-valued GGD by i)(More)
Cytoplasmic dynein is a microtubule-based motor protein complex that plays important roles in a wide range of fundamental cellular processes, including vesicular transport, mitosis, and cell migration. A single major form of cytoplasmic dynein associates with membranous organelles, mitotic kinetochores, the mitotic and migratory cell cortex, centrosomes,(More)
This article describes a Bayesian approach to estimating the spectral density of a stationary time series. A nonparametric prior on the spectral density is described through Bernstein polynomials. Because the actual likelihood is very complicated, a pseudoposterior distribution is obtained by updating the prior using the Whittle likelihood. A Markov chain(More)
Knowing the statistical properties of a complex-valued signal is important in many signal processing applications by providing the necessary information for choosing the appropriate algorithm. In this paper, we provide generalized likelihood ratio tests (GLRT), based on the complex generalized Gaussian distribution (CGGD), for detecting two important signal(More)
We present a framework for discovering acoustic units and generating an associated pronunciation lexicon from an initial grapheme-based recognition system. Our approach consists of two distinct contributions. First, context-dependent grapheme models are clustered using a spectral clustering approach to create a set of phone-like acoustic units. Next, we(More)
A state of the art Speaker Identification (SI) system requires a robust feature extraction unit followed by a speaker modeling scheme for generalized representation of these features. Over the years, Mel-Frequency Cepstral Coefficients (MFCC) modeled on the human auditory system has been used as a standard acoustic feature set for SI applications. However,(More)
Human alteration of large rivers is commonplace, often resulting in significant changes in flow characteristics. We used a time series approach to examine daily mean flow data from locations throughout the mainstem Missouri River. Data from a pre-alteration period (1925–1948) were compared with a post-alteration period (1967–1996), with separate analyses(More)
Speaker verification (SV) on portable devices like smartphones is gradually becoming popular. In this context, two issues need to be considered: 1) such devices have relatively limited computation resources, and 2) they are liable to be used everywhere, possibly in very noisy, uncontrolled environments. This work aims to address both these issues by(More)