objective1TV

1-D Total Variation Penalized Objective Function

Utilities for sparse signal recovery suitable for compressed sensing. L1, L2 and TV penalties, DFT basis matrix, simple sparse signal generator, mutual cumulative coherence between two matrices and examples, Lp complex norm, scaling back regression coefficients.

Mehmet Suzen

R1magic

Compressive Sampling: Sparse Signal Recovery Utilities

objective1TV function

<dl> <dt>x</dt>
<dd>Initial value of the vector to be recovered. Sparse representation 
 of the vector ( N x 1 matrix ) X=Tx, where X is the original vector</dd> <dt>T</dt>
<dd>sparsity bases ( N x N matrix )</dd> <dt>phi</dt>
<dd>Measurement matrix (M x N).</dd> <dt>y</dt>
<dd>Measurement vector (Mx1).</dd> <dt>lambda</dt>
<dd>Penalty coefficient.</dd></dl>

Arguments

Author

1-D Total Variation Penalized Objective Function — objective1TV

<dl>

 <dt>x</dt>
<dd>Initial value of the vector to be recovered. Sparse representation 
 of the vector ( N x 1 matrix ) X=Tx, where X is the original vector</dd>

 <dt>T</dt>
<dd>sparsity bases ( N x N matrix )</dd>

 <dt>phi</dt>
<dd>Measurement matrix (M x N).</dd>

 <dt>y</dt>
<dd>Measurement vector (Mx1).</dd>

 <dt>lambda</dt>
<dd>Penalty coefficient.</dd>

</dl>

objective1TV: 1-D Total Variation Penalized Objective Function

Description

Usage

Value

Arguments

Author