Thomas Blumensath - Iterative Hard Thresholding: Theory and Practice
Iterative Hard Thresholding: Theory and Practice N I V ER
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T. Blumensath Institute for Digital Communications Joint Research Institute for Signal and Image Processing The University of Edinburgh February, 2009
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y = Φx + e
What to Expect I) Iterative Hard Thresholding for Sparse Inverse Problems What’s the probelm?
II) Theory and Practice Nice theory, bad attitude
III) Stability Beyond the Grave (RIP) Operating beyond the limits
IV) Results Up there with the best
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y = Φx + e
PART 1
Iterative Hard Thresholding for Sparse Inverse Problems
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2 of 20
y = Φx + e
The Problem and Solution THE PROBLEM: Given
y = Φx + e, where y ∈ RM , x ∈ RN , Φ ∈ RM ×N and e is observation noise, estimate x given y and Φ when M
S
TH
Y IT
E
U
R
G
H
O F
E
D I U N B
T. Blumensath Institute for Digital Communications Joint Research Institute for Signal and Image Processing The University of Edinburgh February, 2009
home
·
prev
·
next
·
page
y = Φx + e
What to Expect I) Iterative Hard Thresholding for Sparse Inverse Problems What’s the probelm?
II) Theory and Practice Nice theory, bad attitude
III) Stability Beyond the Grave (RIP) Operating beyond the limits
IV) Results Up there with the best
home
·
prev
·
next
·
page
1 of 20
y = Φx + e
PART 1
Iterative Hard Thresholding for Sparse Inverse Problems
home
·
prev
·
next
·
page
2 of 20
y = Φx + e
The Problem and Solution THE PROBLEM: Given
y = Φx + e, where y ∈ RM , x ∈ RN , Φ ∈ RM ×N and e is observation noise, estimate x given y and Φ when M
