EURASIP Journal on Advances in Signal Processing

Papers
(The H4-Index of EURASIP Journal on Advances in Signal Processing is 19. The table below lists those papers that are above that threshold based on CrossRef citation counts [max. 250 papers]. The publications cover those that have been published in the past four years, i.e., from 2022-01-01 to 2026-01-01.)
ArticleCitations
Correction: Quantization-aware sampling set selection for bandlimited graph signals94
Unlicensed assisted transmission in vehicular edge computing networks65
Intelligent radar HRRP target recognition based on CNN-BERT model57
Force estimation for human–robot interaction using electromyogram signals from varied arm postures41
Multi-user communications for line-of-sight large intelligent surface systems35
‘Almost nonunique’ solutions to parameter estimation in periodic signals30
DQN-based resource allocation for NOMA-MEC-aided multi-source data stream30
A signal enhancement method based on the reverberation statistical information28
Resilient data-driven non-intrusive load monitoring for efficient energy management using machine learning techniques28
Blind CFO estimation based on weighted subspace fitting criterion with fuzzy adaptive gravitational search algorithm27
Dual-game based UAV swarm obstacle avoidance algorithm in multi-narrow type obstacle scenarios25
Time delay estimation method based on generalized logarithmic hyperbolic secant function in impulsive noise25
Low-complexity signal detection networks based on Gauss-Seidel iterative method for massive MIMO systems24
Secure and privacy-preserving issues in integrated sensing and communication-enabled wireless networks: a survey24
Deep video-based person re-identification (Deep Vid-ReID): comprehensive survey24
Enhanced rain removal network with convolutional block attention module (CBAM): a novel approach to image de-raining23
TLGRU: time and location gated recurrent unit for multivariate time series imputation23
Deep reinforcement learning-based adaptive modulation for OFDM underwater acoustic communication system23
Seal call recognition based on general regression neural network using Mel-frequency cepstrum coefficient features21
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