Sonar systems are widely used for underwater sensing applications such as navigation, target detection, and environmental monitoring. However, conventional sonar signal processing techniques often rely on handcrafted features and model-based assumptions, which can limit performance in complex and noisy underwater environments. In recent years, learning-based approaches, particularly those using neural networks, have gained increasing attention …

A Review of Learning-Based Sonar Signal Processing Using Neural NetworksRead More

Sonar Acoustic feedback remains a critical limitation in sound reinforcement and communication systems, particularly in environments where microphones and loudspeakers operate close proximity. Traditional suppression methods such as notch filtering, phase shifting, and frequency shifting provide partial relief but often introduce latency, tonal coloration, and reduced audio quality. Recent work has increasingly explored adaptive approaches …

FPGA-Based Acoustic Feedback Suppression A Review of Algorithms, Implementations, and Future DirectionsRead More

The increasing penetration of large-scale photovoltaic power plants has intensified the challenge of managing power variability caused by rapid changes in solar irradiance. Short term and ultra short-term power fluctuations, mainly driven by cloud movement, can lead to severe ramp rate violations and grid instability, particularly in weak and island power systems. This review critically …

A Comprehensive Review of Vision-Based and Data-Driven Solar Power Forecasting TechniquesRead More