  In this Letter, we propose a low-complexity estimator for the correlation
coefficient based on the signed $\operatorname{AR}(1)$ process. The introduced
approximation is suitable for implementation in low-power hardware
architectures. Monte Carlo simulations reveal that the proposed estimator
performs comparably to the competing methods in literature with maximum error
in order of $10^{-2}$. However, the hardware implementation of the introduced
method presents considerable advantages in several relevant metrics, offering
more than 95% reduction in dynamic power and doubling the maximum operating
frequency when compared to the reference method.
