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The estimation of a sparse vector in the linear model is a fundamental problem in signal processing, statistics, and compressive sensing. This paper establishes a lower bound on the mean-squared error...
Sparse Vector Autoregressive Modeling
vector autoregressive (VAR) model sparsity partial spectral coherence (PSC) model selection.
2012/9/18
The vector autoregressive (VAR) model has been widely used for modeling temporal de-pendence in a multivariate time series. For large (and even moderate) dimensions, the number of AR coefficients can ...
Coherence-Based Performance Guarantees for Estimating a Sparse Vector Under Random Noise
Coherence-Based Performance Guarantees Sparse Vector Random Noise
2010/3/19
We consider the problem of estimating a deterministic
sparse vector x0 from underdetermined measurements
Ax0 + w, where w represents white Gaussian noise and A is
a given deterministic dictionary. ...