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Basis pursuit is the mathematical optimization problem of the form: : where ''x'' is a ''N'' × 1 solution vector (signal), ''y'' is a ''M'' × 1 vector of observations (measurements), ''A'' is a ''M'' × ''N'' transform matrix (usually measurement matrix) and ''M'' < ''N''. It is usually applied in cases where there is an underdetermined system of linear equations ''y'' = ''Ax'' that must be exactly satisfied, and the sparsest solution in the ''L''1 sense is desired. When it is desirable to trade off exact congruence of ''Ax'' and ''y'' in exchange for a sparser ''x'', basis pursuit denoising is preferred. == See also == *Compressed sensing *Group testing *Matching pursuit *Sparse approximation 抄文引用元・出典: フリー百科事典『 ウィキペディア（Wikipedia）』 ■ウィキペディアで「basis pursuit」の詳細全文を読む スポンサード リンク
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