Diffusion improved multiband-structured subband adaptive filter algorithms with dynamic selection of regressors and subbands over distributed networks

被引:1
|
作者
Abadi, Mohammad Shams Esfand [1 ]
Ahmadi, Mohammad Javad [1 ]
Shafiee, Mohammad Saeed [1 ]
机构
[1] Shahid Rajaee Teacher Training Univ, Fac Elect Engn, POB 16785-163, Tehran 1678815811, Iran
关键词
diffusion network; distributed estimation; dynamic selection; IMSAFs; improved multiband-structured subband adaptive filter; mean-square performance; LEAST-MEAN SQUARES; SENSOR NETWORKS; FORMULATION; STRATEGIES;
D O I
10.1504/IJSNET.2019.103500
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
The present study solves the problem of distributed estimation in the diffusion networks based on the family of improved multiband-structured subband adaptive filters (IMSAFs). The diffusion IMSAF (DIMSAF), the DIMSAF with dynamic selection of regressors (DIMSAF-DSR), and the DIMSAF with dynamic selection of subbands (DIMSAF-DSS) are established. The DIMSAF-DSS and the DIMSAF-DSR algorithms, while benefiting from high convergence speed in DIMSAF, have lower computational complexity and lower steady-state error. During the weight coefficients adaptation in DIMSAF-DSR, the input signal regressors are dynamically selected at each subband of different nodes. In DIMSAF-DSS, the subbands are dynamically selected at each node. In the following, the introduced algorithms are established based on a general update equation. Accordingly, the mean-square performance analysis of the algorithms is studied in a unified way. The theoretical results and the good performance of proposed algorithms are justified by several computer simulations in adaptive diffusion networks.
引用
收藏
页码:253 / 264
页数:12
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