D
Diego B. Haddad
Researcher at Centro Federal de Educação Tecnológica de Minas Gerais
Publications - 90
Citations - 516
Diego B. Haddad is an academic researcher from Centro Federal de Educação Tecnológica de Minas Gerais. The author has contributed to research in topics: Adaptive filter & Least mean squares filter. The author has an hindex of 11, co-authored 80 publications receiving 337 citations. Previous affiliations of Diego B. Haddad include Centro Federal de Educação Tecnológica Celso Suckow da Fonseca & Universidade Tecnológica Federal do Paraná, Medianeira.
Papers
More filters
Journal ArticleDOI
Mean-square error and stability analysis of a subband structure for the rapid identification of sparse impulse responses
TL;DR: The steady-state mean-square error (MSE) and the maximum value of the step-size @b that allows convergence of the subband PNLMS-type algorithm are analyzed and results results in an algorithm with better convergence rate for sparse systems and colored input signals.
Proceedings ArticleDOI
A Deep Reinforcement Learning Approach to Asset-Liability Management
TL;DR: This paper addresses an ALM problem with a variation of Deep Deterministic Policy Gradient algorithm, and shows that the Reinforcement Learning framework is well fitted to solve this kind of problem, and has the additional benefit of using continuous state spaces.
Journal ArticleDOI
Acoustic Sensor Self-Localization: Models and Recent Results
Diego B. Haddad,Markus V. S. Lima,Wallace A. Martins,Luiz W. P. Biscainho,Leonardo O. Nunes,Bowon Lee +5 more
TL;DR: This paper highlights mobile device self-localization relying exclusively on acoustic signals, but with previous knowledge of reference signals and source positions, and proposes a novel ASL method that combines most of the previous material, whose performance is assessed in a real-world example.
Journal ArticleDOI
A Family of Adaptive Volterra Filters Based on Maximum Correntropy Criterion for Improved Active Control of Impulsive Noise
Guttikonda Gowtham,Srikanth Burra,Asutosh Kar,Jan Ostergaard,Pitikhate Sooraksa,Vladimir Mladenovic,Diego B. Haddad +6 more
TL;DR: This work proposes a family of adaptive algorithms for ANC systems that employ a second-order Volterra filter for accurate modeling of the impulsive disturbances, and utilizes the maximum correntropy criterion as the cost function to improve the adaptive filtering process.
Journal ArticleDOI
Hybrid data augmentation method for combined failure recognition in rotating machines
Dionisio Henrique Carvalho de Sá Só Martins,Amaro A. de Lima,Milena F. Pinto,Douglas O. Hemerly,Thiago de M. Prego,Fabrício L. e Silva,Luís Tarrataca,Ulisses A. Monteiro,Ricardo H. R. Gutiérrez,Diego B. Haddad +9 more