Diffusion LMS Strategies in Sensor Networks With Noisy Input Data
Diffusion LMS Strategies in Sensor Networks With Noisy Input Data
We investigate the performance of distributed least-mean square (LMS) algorithms for parameter estimation over sensor networks where the regression data of each node are corrupted by white measurement noise. Under this condition, we show that the estimates produced by distributed LMS algorithms will be biased if the regression noise is …