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When data symbols modulate a signature waveform /pattern to move across a channel in the presence of disturbance, the signature/spreading-code that maximizes the signal-to-interference-plus-noise ratio (SINR) at the output of the maximum-SINR filter is the smallest-eigenvalue eigenvector of the disturbance autocovariance matrix. In digital communication systems, however, the signature alphabet is finite and digital signature optimization is NP-hard. In this paper, we will present a formal search procedure of cost linear in the signature code length that returns the maximum-SINR binary signature near cords of least SINR decrease in the Euclidean vector space. The quality of the proposed adaptive binary design will be compared against the theoretical upper bound of the complex/real eigenvector maximizer.