Shuqiang Yang, Zhaodi Wang, Huafeng Qin, Yike Liu, Junqiang Wang
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引用次数: 0
Abstract
Finger vein recognition, like control systems, requires harmonizing local and global dynamics for optimal performance. To address limitations in existing methods, we propose the wavelet-transformer algorithm, combining CNNs for local feature extraction, vision transformers (ViT) for global dependency modeling, and discrete wavelet transforms (DWT) for time-frequency analysis. This modular design mirrors control theory principles, ensuring stability and adaptability. Experiments on FV210 and FV618 datasets show the algorithm's superior performance, achieving recognition accuracies of 99.53% and 97.62%, with equal error rates of 0.35% and 0.71%, highlighting its robustness for intelligent recognition and control applications.
期刊介绍：
Electronics Letters is an internationally renowned peer-reviewed rapid-communication journal that publishes short original research papers every two weeks. Its broad and interdisciplinary scope covers the latest developments in all electronic engineering related fields including communication, biomedical, optical and device technologies. Electronics Letters also provides further insight into some of the latest developments through special features and interviews.
Scope
As a journal at the forefront of its field, Electronics Letters publishes papers covering all themes of electronic and electrical engineering. The major themes of the journal are listed below.
Antennas and Propagation
Biomedical and Bioinspired Technologies, Signal Processing and Applications
Control Engineering
Electromagnetism: Theory, Materials and Devices
Electronic Circuits and Systems
Image, Video and Vision Processing and Applications
Information, Computing and Communications
Instrumentation and Measurement
Microwave Technology
Optical Communications
Photonics and Opto-Electronics
Power Electronics, Energy and Sustainability
Radar, Sonar and Navigation
Semiconductor Technology
Signal Processing
MIMO
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