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Human action recognition (HAR) based on WiFi channel state information (CSI) has attracted growing attention due to its contactless, privacy-preserving, and cost-effective nature. Recent studies have reported promising results by leveraging deep lear...

Ham radio has long been a foundational area of practice in electrical engineering. Advances in signal processing, particularly the advent of software-defined radio (SDR), have revolutionized the field, offering new possibilities and modes of operatio...

Burst traffic radio systems use short signal bursts, which are prepended with an a priori known preamble sequence. The burst receivers exploit these preamble sequences for burst start detection. The process of burst start detection is commonly known...

Acoustic scattering is a highly effective tool for non-destructive control and structural analysis. In many real-world applications, understanding acoustic scattering is essential for accurately detecting and characterizing defects, assessing materia...

This study presents a method for deriving closed-form solutions for Lagrange multipliers in worst-case performance optimization (WCPO) beamforming. By approximating the array-received signal autocorrelation matrix as a rank-1 Hermitian matrix using t...

This study investigated the transformative potential of Compressive Sensing (CS) for optimizing multimodal biomedical signal fusion in Wireless Body Sensor Networks (WBSN), specifically targeting challenges in data storage, power consumption, and tra...

Autonomous driving has emerged as a rapidly advancing field in both industry and academia over the past decade. Among the enabling technologies, computer vision (CV) has demonstrated high accuracy across various domains, making it a critical componen...

Decoding motor imagery (MI) of lower-limb movements from electroencephalography (EEG) signals remains a challenge due to the involvement of deep cortical regions, limiting the applicability of Brain–Computer Interfaces (BCIs). This study propos...

Modern healthcare systems are under growing strain from aging populations, urbanization, and rising chronic disease burdens, creating an urgent need for real-time monitoring and informed decision-making. This survey examines how the convergence of In...

This paper presents a method for recognizing sign language gestures corresponding to fruit names using electromyography (EMG) signals. The proposed system focuses on classification using a limited number of EMG channels, aiming to reduce classificati...