Blind separation and blind deconvolution: an information-theoretic approach
نویسندگان
چکیده
INFORMATION-THEORETIC APPROACH Anthony J. Bell and Terrence J. Sejnowski Computational Neurobiology Laboratory, The Salk Institute, 10010 N. Torrey Pines Road, La Jolla, California 92037
منابع مشابه
Information Theoretic Learning
of Dissertation Presented to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy INFORMATION THEORETIC LEARNING: RENYI’S ENTROPY AND ITS APPLICATIONS TO ADAPTIVE SYSTEM TRAINING By Deniz Erdogmus May 2002 Chairman: Dr. Jose C. Principe Major Department: Electrical and Computer Engineering Traditionally, second-order ...
متن کاملPSO-Optimized Blind Image Deconvolution for Improved Detectability in Poor Visual Conditions
Abstract: Image restoration is a critical step in many vision applications. Due to the poor quality of Passive Millimeter Wave (PMMW) images, especially in marine and underwater environment, developing strong algorithms for the restoration of these images is of primary importance. In addition, little information about image degradation process, which is referred to as Point Spread Function (PSF...
متن کاملSemiparametric Approach to Blind Separation of Dynamic Systems
| In this paper we present a semipara-metric approach to blind separation of nonlinear dy-namical systems with linear output equations. First we formulate blind deconvolution in a framework of semiparametric model and derive a family of estimating functions for the blind separation problem by using a nonholonomic reparametrization. The natural gradient learning algorithm is derived in the semip...
متن کاملOn Information Maximization and Blind Signal Deconvolution
In the following paper we investigate two algorithms for blind signal deconvolution that has been proposed in the literature. We derive a clear interpretation of the information theoretic objective function in terms of signal processing and show that only one is appropriate to solve the deconvolution problem, while the other will only work if the unknown filter is constrained to be minimum phas...
متن کاملA Data-Derived Quadratic Independence Measure for Adaptive Blind Source Recovery in Practical Applications
We present a novel performance index to measure the statistical independence of data sequences and apply it to the framework of blind source recovery (BSR) that includes blind source separation, deconvolution and equalization. This performance index is capable of measuring the mutual independence of data sequences directly from the data. This information theoretic; Quadratic Independence Measur...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 1995