Title :
Performance of diffusion adaptation for collaborative optimization
Author :
Chen, Jianshu ; Sayed, Ali H.
Author_Institution :
Dept. of Electr. Eng., Univ. of California, Los Angeles, CA, USA
Abstract :
We derive an adaptive diffusion mechanism to optimize global cost functions in a distributed manner over a network of nodes. The cost function is assumed to consist of the sum of individual components, and diffusion adaptation is used to enable the nodes to cooperate locally through in-network processing in order to solve the desired optimization problem. We analyze the mean-square-error performance of the algorithm, including its transient and steady-state behavior. We illustrate one application in the context of least-mean-squares estimation for sparse vectors.
Keywords :
least mean squares methods; optimisation; sparse matrices; vectors; adaptive diffusion mechanism; collaborative optimization; diffusion adaptation performance; global cost function optimization; in-network processing; least mean squares estimation; mean square error performance; sparse vectors; steady-state behavior; transient behavior; Adaptive systems; Convergence; Cost function; Noise; Steady-state; Vectors; Distributed optimization; diffusion adaptation; energy conservation; in-network processing; learning;
Conference_Titel :
Acoustics, Speech and Signal Processing (ICASSP), 2012 IEEE International Conference on
Conference_Location :
Kyoto
Print_ISBN :
978-1-4673-0045-2
Electronic_ISBN :
1520-6149
DOI :
10.1109/ICASSP.2012.6288733
