Sparse Representations in Signal and Image Processing

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Sparse Representations in Signal and Image Processing

In this issue, we would like to pont to two online courses available via www.edx.org:

1) Sparse Representations in Signal and Image Processing: Fundamentals (https://www.edx.org/course/sparse-representations-signal-image-israelx-236862-1x)

2) Sparse Representations in Image Processing: From Theory to Practice (https://www.edx.org/course/sparse-representations-image-processing-israelx-236862-2x)

The instructors are Dr. Michael Elad (http://www.cs.technion.ac.il/~elad/) and a PhD student, Mr. Yaniv Romano (http://www.cs.technion.ac.il/~yromano/), both from the Technion - Israel Institute of Technology.

In the first course, the instructors will cover the fundamentals of the field of sparse representations, starting with its theoretical concepts, and systematically presenting its key achievements. While the second course will be a follow-up to the first introductory course of sparse representations. Whereas the first course puts emphasis on the theory and algorithms in this field, this course shows how these apply to actual signal and image processing needs.

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