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

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.