Diffusion Least Mean Square: Simulations
This is an incremental analysis for adaptive filtering in networked systems.
The paper analyzes the performance of diffusion strategies applied to the Least-Mean-Square adaptive filter in a network of cooperative agents, finding conditions where diversity in filter parameters improves convergence and stability compared to a non-cooperative agent.
In this technical report we analyse the performance of diffusion strategies applied to the Least-Mean-Square adaptive filter. We configure a network of cooperative agents running adaptive filters and discuss their behaviour when compared with a non-cooperative agent which represents the average of the network. The analysis provides conditions under which diversity in the filter parameters is beneficial in terms of convergence and stability. Simulations drive and support the analysis.