Let be the support of a vector , with . Suppose the null space property holds. Every other feasible vector is , where . Splitting its L1 norm over and and using the triangle inequality gives
Thus the sparse vector is the unique minimizer in basis pursuit. Notice that the argument works for complex coordinates: it uses the absolute value inequality, rather than a real sign function.
Conversely, suppose basis pursuit uniquely recovers every sparse vector of order . Fix and any with . Take and . These vectors have the same measurements, because , and they are distinct since . The vector has at most nonzero coordinates, so uniqueness gives
This is the null space property for every such . Uniform unique recovery by basis pursuit is equivalent to the order- null space property.

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