Learning Filter Bank Sparsifying Transforms
نویسندگان
چکیده
منابع مشابه
Learning Filter Bank Sparsifying Transforms
Data is said to follow the transform (or analysis) sparsity model if it becomes sparse when acted on by a linear operator called a sparsifying transform. Several algorithms have been designed to learn such a transform directly from data, and data-adaptive sparsifying transforms have demonstrated excellent performance in signal restoration tasks. Sparsifying transforms are typically learned usin...
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Recent years have numerous algorithms to learn a sparse synthesis or analysis model from data. Recently, a generalized analysis model called the ’transform model’ has been proposed. Data following the transform model is approximately sparsified when acted on by a linear operator called a sparsifying transform. While existing transform learning algorithms can learn a transform for any vectorized...
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ژورنال
عنوان ژورنال: IEEE Transactions on Signal Processing
سال: 2019
ISSN: 1053-587X,1941-0476
DOI: 10.1109/tsp.2018.2883021