Name
Title | ||
|---|---|---|
Distributed Estimation Over an Adaptive Incremental Network Based on the Affine Projection Algorithm |
Abstract | ||
|---|---|---|
We study the problem of distributed estimation based on the affine projection algorithm (APA), which is developed from Newton's method for minimizing a cost function. The proposed solution is formulated to ameliorate the limited convergence properties of least-mean-square (LMS) type distributed adaptive filters with colored inputs. The analysis of transient and steady-state performances at each individual node within the network is developed by using a weighted spatial-temporal energy conservation relation and confirmed by computer simulations. The simulation results also verify that the proposed algorithm provides not only a faster convergence rate but also an improved steady-state performance as compared to an LMS-based scheme. In addition, the new approach attains an acceptable misadjustment performance with lower computational and memory cost, provided the number of regressor vectors and filter length parameters are appropriately chosen, as compared to a distributed recursive-least-squares (RLS) based method. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1109/TSP.2009.2025074 | IEEE Transactions on Signal Processing |
Keywords | Field | DocType |
least mean square,distributed estimation,steady-state performance,energy conversation,adaptive incremental network,newton method,adaptive filters,convergence rate,recursive least square method,least mean squares methods,weighted spatial-temporal energy conservation relation,affine projection algorithm,proposed algorithm,distributed adaptive filters,memory cost,affine transforms,limited convergence property,acceptable misadjustment performance,proposed solution,cost function,improved steady-state performance,least squares approximation,energy conservation,computer simulation,steady state,adaptive filter,adaptive systems,energy conversion | Convergence (routing),Least mean squares filter,Affine transformation,Mathematical optimization,Recursion (computer science),Control theory,Rate of convergence,Adaptive filter,Mathematics,Computational complexity theory,Newton's method | Journal |
Volume | Issue | ISSN |
58 | 1 | 1053-587X |
Citations | PageRank | References |
13 | 0.73 | 16 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Leilei Li | 1 | 13 | 0.73 |
| Jonathon Chambers | 2 | 868 | 82.37 |
| Cássio Guimarães Lopes | 3 | 394 | 32.32 |
| Ali H. Sayed | 4 | 9134 | 667.71 |