经典的稀疏重构算法，即快速贝叶斯追踪算法，恢复出的信号精度高，恢复算法复杂度低-Classic sparse reconstruction algorithm, namely the bayesian tracking algorithm quickly, to restore the signal of high precision, low recovery algorithm complexity

Compressive sensing (CS) has been proposed for signals with sparsity in a linear transform domain. We explore a signal dependent unknown linear transform, namely the impulse response matrix operating on a sparse excitation, as in the linear model of