Signal Processing

This MATLAB script demonstrates an approach to beamforming and interference suppression in scenarios with multiple users and multiple interferers. It constructs an N-element linear array, computes beamformer weights through a generalized eigen-decomposition of summed desired and interference correlation matrices, and then runs a Monte Carlo simulation to estimate the Signal-to-Interference-plus-Noise Ratio (SINR) for one of the users under random channel conditions.

Cardiac functional imaging plays a crucial role in the detection, diagnosis, and prognosis of major cardiac diseases. Magnetocardiography (MCG) provides the benefits of non-invasive measurement and precise reflection of signals generated by the heart’s contraction and relaxation, and is gaining prominence in medical technology. However, due to various reasons, the reviewed dataset was not available and no standard dataset has been published on this topic.

Walking-friendly cities not only promote health and environmental benefits but also play crucial roles in urban development and local economic revitalization. Generally, pedestrian interviews and surveys used to evaluate walkability, but this is expensive and lack professional insight. To address limitations in current methods for evaluating pedestrian pathways, we propose a novel approach utilizing wearable sensors and deep learning.

In this article, a novel method for interferometric target detection that employs coherent echoes and spatial frequency sampling is proposed. Originating from radio astronomy, interferometric passive microwave imaging has become widely applied for the passive microwave remote sensing of Earth. The proposed technique, termed Interferometric Coherent Echo Detection, is a novel active imaging method that capitalizes on coherent echoes to sample the spatial frequency domain.