Electronics Letters

Papers
(The H4-Index of Electronics Letters is 18. 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 2020-04-01 to 2024-04-01.)
ArticleCitations
Modelling and circuit realisation of a new no‐equilibrium chaotic system with hidden attractor and coexisting attractors71
Motor imagery BCI classification based on novel two‐dimensional modelling in empirical wavelet transform71
Hyperchaos in a second‐order discrete memristor‐based map model68
Music genre classification and music recommendation by using deep learning50
PotNet: Pothole detection for autonomous vehicle system using convolutional neural network45
Diagnosis of autism spectrum disorder from EEG using a time–frequency spectrogram image‐based approach36
Secrecy outage probability analysis for RIS‐assisted NOMA systems31
Classification of emotions from EEG signals using time‐order representation based on the S‐transform and convolutional neural network30
Efficient approach for EEG‐based emotion recognition29
3D printed waveguide step‐twist with bandpass filtering functionality27
6.915-Gbit/s white-light phosphor laser diode-based DCO-OFDM visible light communication (VLC) system with functional transmission distance25
Dop‐NET: a micro‐Doppler radar data challenge25
Closed‐form expressions for spatial correlation parameters for performance analysis of fluid antenna systems24
High‐speed graded‐channel AlGaN/GaN HEMTs with power added efficiency >70% at 30 GHz24
Brain MRI‐based Wilson disease tissue classification: an optimised deep transfer learning approach22
Reliable and efficient PUF‐based cryptographic key generator using bit self‐tests21
An omega‐k algorithm for multireceiver synthetic aperture sonar21
Security embedded dynamic resource allocation model for cloud data centre19
Compact multi‐band chipless RFID resonators for identification and authentication applications18
Automatic hotspots detection based on UAV infrared images for large‐scale PV plant18
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