On the identifiability of overcomplete dictionaries via the minimisation principle underlying K-SVD
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چکیده
منابع مشابه
On the Identifiability of Overcomplete Dictionaries via the Minimisation Principle Underlying K-SVD
This article gives theoretical insights into the performance of K-SVD, a dictionary learning algorithm that has gained significant popularity in practical applications. The particular question studied here is when a dictionary Φ ∈ Rd×K can be recovered as local minimum of the minimisation criterion underlying K-SVD from a set of N training signals yn = Φxn. A theoretical analysis of the problem...
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In recent years there has been a growing interest in the study of sparse representation of signals. Using an overcomplete dictionary that contains prototype signal-atoms, signals are described by sparse linear combinations of these atoms. Applications that use sparse representation are many and include compression, regularization in inverse problems, feature extraction, and more. Recent activit...
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In recent years there has been a growing interest in the study of sparse representation of signals. Using an overcomplete dictionary that contains prototype signal-atoms, signals are described by sparse linear combinations of these atoms. Applications that use sparse representation are many and include compression, regularization in inverse problems, feature extraction, and more. Recent activit...
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ژورنال
عنوان ژورنال: Applied and Computational Harmonic Analysis
سال: 2014
ISSN: 1063-5203
DOI: 10.1016/j.acha.2014.01.005