Some signal reconstruction problems allow for flexibility in the selection of observations and hence the signal formation equation. In such cases, we have the opportunity to determine the best combination of observations before acquiring the data. We analyze the computational complexity of various forms of sequential backward selection (SBS) to select observations. In light of this analysis, we present a computationally improved algorithm for large-scale observation selection problems.
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