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Adaptive algorithms, combinations and applications in deconvolution

Grant number: 12/24835-1
Support type:Regular Research Grants
Duration: March 01, 2013 - February 28, 2015
Field of knowledge:Engineering - Electrical Engineering
Principal Investigator:Magno Teófilo Madeira da Silva
Grantee:Magno Teófilo Madeira da Silva
Home Institution: Escola Politécnica (EP). Universidade de São Paulo (USP). São Paulo , SP, Brazil
Assoc. researchers: Jerónimo Arenas Garcia ; João Mendes Filho ; Marcio Eisencraft ; Maria das Dores dos Santos Miranda ; Vitor Heloiz Nascimento

Abstract

Filter combinations running in parallel have been used to improve the performance of adaptive filters related to the choice of the fixed parameters, tracking capability, stability, steady-state solution, initialization, among other factors. Although many results related to this topic had been published in the literature, there are still many open problems, which will be addressed in this research project, that is: (i) combinations of two NLMS (normalized least mean square) filters with different orders for sparse acoustic echo cancellation; (ii) analysis of the transient of the convex combination; (iii) reduction of the computational cost of the combination; (iv) comparison of the convex, affine and linear combinations in different simulation scenarios; and (v) use of the affine combination in adaptive distributed processing with applications in sensor networks. We also intend to address the use of blind equalization algorithms for QAM (quadrature amplitude modulation) signals in image restoration. Some works in the literature propose the use of the constant modulus algorithm (CMA) for image blind deconvolution. However, its performance is not good enough since the image pixels cannot be interpreted as a constant modulus signal. In this work, we will use efficient blind equalization algorithms for image deconvolution. Finally, we will study equalization in communication systems based in chaos. Due to the lack of robustness of chaos synchronization, even minor channel imperfections are enough to hinder communication. Therefore, the equalizer plays an important role in these systems. Firstly, we will extend the NLMS algorithm to adapt the equalizer and in the sequel we will investigate a possible blind solution. (AU)

Scientific publications (5)
(References retrieved automatically from Web of Science and SciELO through information on FAPESP grants and their corresponding numbers as mentioned in the publications by the authors)
FERNANDEZ-BES, JESUS; ARENAS-GARCIA, JERONIMO; SILVA, MAGNO T. M.; AZPICUETA-RUIZ, LUIS A. Adaptive Diffusion Schemes for Heterogeneous Networks. IEEE TRANSACTIONS ON SIGNAL PROCESSING, v. 65, n. 21, p. 5661-5674, NOV 1 2017. Web of Science Citations: 5.
ARENAS-GARCIA, JERONIMO; AZPICUETA-RUIZ, LUIS A.; SILVA, MAGNO T. M.; NASCIMENTO, VITOR H.; SAYED, ALI H. Combinations of Adaptive Filters. IEEE SIGNAL PROCESSING MAGAZINE, v. 33, n. 1, p. 120-140, JAN 2016. Web of Science Citations: 43.
CANDIDO, RENATO; SORIANO, DIOGO C.; SILVA, MAGNO T. M.; EISENCRAFT, MARCIO. Do chaos-based communication systems really transmit chaotic signals?. Signal Processing, v. 108, p. 412-420, MAR 2015. Web of Science Citations: 7.
FERNANDEZ-BES, JESUS; AZPICUETA-RUIZ, LUIS A.; ARENAS-GARCIA, JERONIMO; SILVA, MAGNO T. M. Distributed estimation in diffusion networks using affine least-squares combiners. DIGITAL SIGNAL PROCESSING, v. 36, p. 1-14, JAN 2015. Web of Science Citations: 12.
CANDIDO, RENATO; EISENCRAFT, MARCIO; SILVA, MAGNO T. M. Channel equalization for synchronization of chaotic maps. DIGITAL SIGNAL PROCESSING, v. 33, p. 42-49, OCT 2014. Web of Science Citations: 5.

Please report errors in scientific publications list by writing to: cdi@fapesp.br.