Title :
Steady-state performance of incremental learning over distributed networks for non-Gaussian data
Author :
Li, Leilei ; Zhang, Yonggang ; Chambers, Jonathon A. ; Sayed, Ali H.
Author_Institution :
Dept. of Electron. & Electr. Eng., Loughborough Univ., Loughborough
Abstract :
In this paper, the steady-state performance of the distributed least mean-squares (dLMS) algorithm within an incremental network is evaluated without the restriction of Gaussian distributed inputs. Computer simulations are presented to verify the derived performance expressions.
Keywords :
adaptive signal processing; least mean squares methods; telecommunication computing; wireless sensor networks; adaptive signal; distributed least mean-square algorithm; distributed sensor network; incremental learning; nonGaussian signal; steady-state performance; Adaptive filters; Adaptive systems; Agriculture; Computer simulation; Data engineering; Electronic mail; Energy conservation; Monitoring; Steady-state; Surveillance; Adaptive filters; distributed estimation; energy conservation; incremental algorithm;
Conference_Titel :
Signal Processing, 2008. ICSP 2008. 9th International Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4244-2178-7
Electronic_ISBN :
978-1-4244-2179-4
DOI :
10.1109/ICOSP.2008.4697112
