Content deleted Content added
No edit summary |
m clean up, added underlinked tag using AWB |
||
Line 1:
{{Underlinked|date=June 2013}}
[[Convex optimization]] is a sub field of optimization which can produce reliable solutions
and can be solved exactly. Many signal processing problems can be formulated as convex
Line 35 ⟶ 37:
</math>
The distance from <math>x \in \mathbb{R}^N</math> to <math>C</math> is defined as
<math>
Line 70 ⟶ 72:
Proximity operators of function <math>f</math> at <math>x</math> is defined as
For every <math>x \in \mathbb{R}^N </math>, the minimization problem,
<math>
Line 83 ⟶ 85:
</math>
The proximity operator of <math>f</math> is characterized by inclusion
<math>
Line 91 ⟶ 93:
</math>
If <math>f</math> is differentiable then above equation reduces to
<math>
Line 112 ⟶ 114:
* [http://en.wikipedia.org/wiki/Alternating_projection Alternating Projection]
* [http://en.wikipedia.org/wiki/Convex_optimization Convex Optimization]
== References ==
| |||