Research

Recently, there has been increasing interest for easy and reliable generation of 3D animated models facilitating several real-time …

This research develops a model-based Bayesian learning approach to efficiently encode dense 3D meshes using compressed sensing, achieving higher compression ratios while preserving visual quality.

A novel supervised energy disaggregation method uses dictionary-based modelling of appliance states to accurately identify and quantify energy consumption patterns in real-world settings.

This research develops an adaptive completion algorithm for wireless sensor networks, preserving privacy while accurately estimating the full-rank correlation matrix.

This paper introduces a novel matrix completion-based approach to distributed beamforming, enabling efficient maximization of receiver SNR while minimizing transmit power and interference.

This paper presents a low-complexity OSIC equalization algorithm for OFDM-based vehicular communications, significantly reducing computational complexity while maintaining robust ICI mitigation performance.

The correlation structure among the sensor observa- tions is a significant characteristic of the wireless sensor network (WSN) which can …

In this paper, we consider the problem of distributed beamforming for maximization of the receiver signal-to-noise­ ratio (SNR) subject …

Vehicular communication systems are usually equipped with orthogonal frequency division multiplexing (OFDM) transceivers that operate …

In this paper , a supervised energy disaggregation method is proposed. The appliances that are monitored, are modelled by multi-state …