Download or read book Maximum Likelihood Estimation of a Class of Non Gaussian Densities with Application to Deconvolution written by Trung T. Pham and published by . This book was released on 1987 with total page 6 pages. Available in PDF, EPUB and Kindle. Book excerpt: This paper investigates in detail the properties of the maximum likelihood estimator of the generalized p-Gaussian (gpG) probability density function (pdf) from N independent identically distributed (iid) samples, especially in the context of the deconvolution problem under gpG white noise. The first part describes the properties of the estimator independently on the application. The second part obtains the solution of the above mentioned deconvolution problem as the solution of a minimum norm problem in an l sub p normed space. In the present paper, we show that such a minimum norm solution is the maximum likelihood estimate is unbiased, with the lower bound of the variance of the error equal to the Cramer Rao lower bound, and the upper bound derived from the concept of a generalized inverse.

Download or read book ICASSP 87 written by and published by . This book was released on 1987 with total page 690 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Handbook of Mathematical Methods in Imaging written by Otmar Scherzer and published by Springer Science & Business Media. This book was released on 2010-11-23 with total page 1626 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Handbook of Mathematical Methods in Imaging provides a comprehensive treatment of the mathematical techniques used in imaging science. The material is grouped into two central themes, namely, Inverse Problems (Algorithmic Reconstruction) and Signal and Image Processing. Each section within the themes covers applications (modeling), mathematics, numerical methods (using a case example) and open questions. Written by experts in the area, the presentation is mathematically rigorous. The entries are cross-referenced for easy navigation through connected topics. Available in both print and electronic forms, the handbook is enhanced by more than 150 illustrations and an extended bibliography. It will benefit students, scientists and researchers in applied mathematics. Engineers and computer scientists working in imaging will also find this handbook useful.

Download or read book Technical Reports Awareness Circular TRAC written by and published by . This book was released on 1987-08 with total page 566 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Energy Minimization Methods in Computer Vision and Pattern Recognition written by Edwin R. Hancock and published by Springer. This book was released on 2003-07-31 with total page 345 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the Second International Workshop on Energy Minimization Methods in Computer Vision and Pattern Recognition, EMMCVPR'99, held in York, UK in July 1999. The book presents 11 revised full papers together with 11 papers presented at the meeting as posters. Those papers were selected from a total of 33 submissions. The book is divided in sections on shape, minimum description length, Markov random fields, contours, search and consistent labeling, tracking and video, and biomedical applications.

Download or read book Signal Processing Theories and Applications written by and published by . This book was released on 1988 with total page 668 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Proceedings written by and published by . This book was released on 1996 with total page 464 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Signal Processing IV written by and published by . This book was released on 1988 with total page 668 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Blind Image Deconvolution written by Patrizio Campisi and published by CRC Press. This book was released on 2017-12-19 with total page 421 pages. Available in PDF, EPUB and Kindle. Book excerpt: Blind image deconvolution is constantly receiving increasing attention from the academic as well the industrial world due to both its theoretical and practical implications. The field of blind image deconvolution has several applications in different areas such as image restoration, microscopy, medical imaging, biological imaging, remote sensing, astronomy, nondestructive testing, geophysical prospecting, and many others. Blind Image Deconvolution: Theory and Applications surveys the current state of research and practice as presented by the most recognized experts in the field, thus filling a gap in the available literature on blind image deconvolution. Explore the gamut of blind image deconvolution approaches and algorithms that currently exist and follow the current research trends into the future. This comprehensive treatise discusses Bayesian techniques, single- and multi-channel methods, adaptive and multi-frame techniques, and a host of applications to multimedia processing, astronomy, remote sensing imagery, and medical and biological imaging at the whole-body, small-part, and cellular levels. Everything you need to step into this dynamic field is at your fingertips in this unique, self-contained masterwork. For image enhancement and restoration without a priori information, turn to Blind Image Deconvolution: Theory and Applications for the knowledge and techniques you need to tackle real-world problems.

Download or read book Deconvolution Problems in Nonparametric Statistics written by Alexander Meister and published by Springer Science & Business Media. This book was released on 2009-12-24 with total page 211 pages. Available in PDF, EPUB and Kindle. Book excerpt: Deconvolution problems occur in many ?elds of nonparametric statistics, for example, density estimation based on contaminated data, nonparametric - gression with errors-in-variables, image and signal deblurring. During the last two decades, those topics have received more and more attention. As appli- tions of deconvolution procedures concern many real-life problems in eco- metrics, biometrics, medical statistics, image reconstruction, one can realize an increasing number of applied statisticians who are interested in nonpa- metric deconvolution methods; on the other hand, some deep results from Fourier analysis, functional analysis, and probability theory are required to understand the construction of deconvolution techniques and their properties so that deconvolution is also particularly challenging for mathematicians. Thegeneraldeconvolutionprobleminstatisticscanbedescribedasfollows: Our goal is estimating a function f while any empirical access is restricted to some quantity h = f?G = f(x?y)dG(y), (1. 1) that is, the convolution of f and some probability distribution G. Therefore, f can be estimated from some observations only indirectly. The strategy is ˆ estimating h ?rst; this means producing an empirical version h of h and, then, ˆ applying a deconvolution procedure to h to estimate f. In the mathematical context, we have to invert the convolution operator with G where some reg- ˆ ularization is required to guarantee that h is contained in the invertibility ˆ domain of the convolution operator. The estimator h has to be chosen with respect to the speci?c statistical experiment.

Download or read book Journal of VLSI Signal Processing Systems for Signal Image and Video Technology written by and published by . This book was released on 2007 with total page 528 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Variational and Scale Mixture Representations of Non Gaussian Densities for Estimation in the Bayesian Linear Model written by Jason Allan Palmer and published by . This book was released on 2006 with total page 150 pages. Available in PDF, EPUB and Kindle. Book excerpt: This thesis considers representations of non-Gaussian probability densities for use in various estimation problems associated with the Bayesian Linear Model. We define a class of densities that we call Strongly Super-Gaussian, and show the relationship of these densities to Gaussian Scale Mixtures, and densities with positive kurtosis. Such densities have been used to model "sparse" random variables, with densities that are sharply peaked with heavy tails. We show that strongly super-Gaussian densities are natural generalizations of Gaussian densities, and permit the derivation of monotonic iterative algorithms for parameter estimation in sparse coding in overcomplete signal dictionaries, blind source separation, independent component analysis, and blind multichannel deconvolution. Mixtures of strongly super-Gaussian densities can be used to model arbitrary densities with greater economy that a Gaussian mixture model. The framework is extended to multivariate dependency models for independent subspace analysis. We apply the methods to the estimation of neural electro-magnetic sources from electro-encephalogram recordings, and to sparse coding of images.

Download or read book Gaussian and Non Gaussian Linear Time Series and Random Fields written by Murray Rosenblatt and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 252 pages. Available in PDF, EPUB and Kindle. Book excerpt: The principal focus here is on autoregressive moving average models and analogous random fields, with probabilistic and statistical questions also being discussed. The book contrasts Gaussian models with noncausal or noninvertible (nonminimum phase) non-Gaussian models and deals with problems of prediction and estimation. New results for nonminimum phase non-Gaussian processes are exposited and open questions are noted. Intended as a text for gradutes in statistics, mathematics, engineering, the natural sciences and economics, the only recommendation is an initial background in probability theory and statistics. Notes on background, history and open problems are given at the end of the book.

Download or read book Nonparametric Estimation under Shape Constraints written by Piet Groeneboom and published by Cambridge University Press. This book was released on 2014-12-11 with total page 429 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book introduces basic concepts of shape constrained inference and guides the reader to current developments in the subject.

Download or read book Scientific and Technical Aerospace Reports written by and published by . This book was released on 1994 with total page 584 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book ICASSP 88 written by and published by . This book was released on 1988 with total page 760 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Nonparametric Probability Density Estimation written by Richard A. Tapia and published by . This book was released on 1978 with total page 196 pages. Available in PDF, EPUB and Kindle. Book excerpt: