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20122025
most citedAdaptive Minimum BER Reduced-Rank Linear Detection for Massive MIMO Systems

6 citations · 29 across the 106 of their papers we have counts for

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9 papers · 1 filter

cs.LG2022

Sparsity-Aware Robust Normalized Subband Adaptive Filtering algorithms based on Alternating Optimization

Yi Yu, Zongxin Huang, Hongsen He +2

This paper proposes a unified sparsity-aware robust normalized subband adaptive filtering (SA-RNSAF) algorithm for identification of sparse systems under impulsive noise. The propo…

cs.LG2022

Conjugate Gradient Adaptive Learning with Tukey's Biweight M-Estimate

Lu Lu, Yi Yu, Rodrigo C. de Lamare +1

We propose a novel M-estimate conjugate gradient (CG) algorithm, termed Tukey's biweight M-estimate CG (TbMCG), for system identification in impulsive noise environments. In partic…

cs.LG2021

Robust Adaptive Filtering Based on Exponential Functional Link Network

T. Yu, W. Li, Y. Yu +1

The exponential functional link network (EFLN) has been recently investigated and applied to nonlinear filtering. This brief proposes an adaptive EFLN filtering algorithm based on…

cs.LG2020

Study of Energy-Efficient Distributed RLS-based Learning with Coarsely Quantized Signals

A. Danaee, R. C. de Lamare, V. H. Nascimento

In this work, we present an energy-efficient distributed learning framework using coarsely quantized signals for Internet of Things (IoT) networks. In particular, we develop a dist…

cs.LG2020

Study of Diffusion Normalized Least Mean M-estimate Algorithms

Y. Yu, H. He, T. Yang +2

This work proposes diffusion normalized least mean M-estimate algorithm based on the modified Huber function, which can equip distributed networks with robust learning capability i…

cs.LG2019

Compressed Sensing with Probability-based Prior Information

Q. Jiang, S. Li, Z. Zhu +3

This paper deals with the design of a sensing matrix along with a sparse recovery algorithm by utilizing the probability-based prior information for compressed sensing system. With…