access icon free Incremental M-estimate-based least-mean algorithm over distributed network

An incremental least-mean M-estimate algorithm is proposed for distributed network, which minimises a robust M-estimator-based cost function against impulsive noise via the gradient descent method. Moreover, based on the same frame for implementation, an incremental distributed least-mean p-power algorithm is presented for combating impulsive noise. Simulations verify the superiority of the proposed algorithms in the presence of impulsive noise relative to some existing incremental distributed algorithms.

Inspec keywords: gradient methods; least mean squares methods; impulse noise; wireless sensor networks; adaptive filters

Other keywords: gradient descent method; distributed adaptive filtering algorithm; incremental distributed least-mean p-power algorithm; incremental distributed algorithm; robust M-estimator-based cost function; impulsive noise; distributed network; incremental M-estimate-based least-mean algorithm; wireless sensor network

Subjects: Filtering methods in signal processing; Interpolation and function approximation (numerical analysis); Wireless sensor networks

http://iet.metastore.ingenta.com/content/journals/10.1049/el.2016.1190
Loading

Related content

content/journals/10.1049/el.2016.1190
pub_keyword,iet_inspecKeyword,pub_concept
6
6
Loading