cr.sparse.block.bsbl.bsbl_bo_jit¶
- cr.sparse.block.bsbl.bsbl_bo_jit(Phi, y, blk_len, options=BSBL_Options(learn_block_corr=1, learn_lambda=1, prune_gamma=0.001, lambda_val=1e-12, max_iters=800, epsilon=1e-08))¶
Reconstructs a block sparse signal using BSBL-BO algorithm
- Parameters
Phi (jax.numpy.ndarray) – Sensing matrix
y (jax.numpy.ndarray) – Measurement vector
blk_len (int) – Length/size of each block
options (BSBL_Options) – Options for algorithm execution
- Returns
Solution of the sparse recovery problem
- Return type
Note
Phi must be a matrix. Linear operators are not supported since we need to break Phi down into submatrices for each block.
Use
bsbl_bo_options()
to initialize options for the algorithm.
Examples