Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: As an important extension to sparsity, Block Structured Sparsity (BSS) has been widely investigated and a large set of algorithms have been designed to recover signals with BSS. , a dynamic system is proposed to recover signals with BSS, namely D-BSS. Particularly, D-BSS turns to exploiting the dynamic systems governed by an ź 2 , 1 norm constraint. It can be proved that the equilibrium of D-BSS is equivalent to optimum of traditional BSS algorithms, e.g., Group-lasso. Simulation results are given to illustrate the desirable performance of the D-BSS system, especially the improvement of convergence rate. HighlightsPropose a dynamic system (D-BSS) combining with the structure information to solve the sparse recovery problem.The D-BSS is equivalent to the classical algorithm of group-lasso.The observation number needed of D-BSS is smaller.The convergence rate of D-BSS is faster.
['Junying Ren', 'Chen Wei', 'Lei Yu', 'Haijian Zhang', 'Hong Sun']
I am writing a research paper on a idea Dynamic recovery for block sparse signals
[{"from": "human", "value": "I am writing a research paper on a idea Dynamic recovery for block sparse signals"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: As an important extension to sparsity, Block Structured Sparsity (BSS) has been widely investigated and a large set of algorithms have been designed to recover signals with BSS. , a dynamic system is proposed to recover signals with BSS, namely D-BSS. Particularly, D-BSS turns to exploiting the dynamic systems governed by an \u017a 2 , 1 norm constraint. It can be proved that the equilibrium of D-BSS is equivalent to optimum of traditional BSS algorithms, e.g., Group-lasso. Simulation results are given to illustrate the desirable performance of the D-BSS system, especially the improvement of convergence rate. HighlightsPropose a dynamic system (D-BSS) combining with the structure information to solve the sparse recovery problem.The D-BSS is equivalent to the classical algorithm of group-lasso.The observation number needed of D-BSS is smaller.The convergence rate of D-BSS is faster."}]