287+ open-access research outputs.
Electrooculogram (EOG) is a non-invasive bio-signal generated by the potential difference between the retina and cornea during eye movement, and is widely utilized in Human-Computer Interaction (HCI) โฆ
Existing cyberattack detection methods for smart grids such as Artificial Neural Networks (ANNs) and Deep Reinforcement Learning (DRL) often suffer from limited adaptability, delayed response, and inaโฆ
The concept of positively invariant (PI) sets has proven effective in the formal verification of stability and safety properties for autonomous systems. However, the characterization of such sets is cโฆ
Accurate building energy models are crucial for analyzing sector-coupled energy systems, where buildings interact with electrified heating, energy storage, and advanced control across various scenarioโฆ
Camera pipelines receive raw Bayer-format frames that need to be denoised, demosaiced, and often super-resolved. Multiple frames are captured to utilize natural hand tremors and enhance resolution. Muโฆ
Spiking Neural Networks (SNNs) offer an energy efficient alternative to conventional Artificial Neural Networks (ANNs) but typically still require a large number of parameters. This work introduces Liโฆ
Reliable control and state estimation of differential drive robots (DDR) operating in dynamic and uncertain environments remains a challenge, particularly when system dynamics are partially unknown anโฆ
Stacked intelligent metasurfaces (SIMs) represent a breakthrough in wireless hardware by comprising multilayer, programmable metasurfaces capable of analog computing in the electromagnetic (EM) wave dโฆ
Nonlinear system identificationhas proven to be effective in obtaining accurate models from data for complex real-world systems. In particular, recent encoder-based methods with artificial neural netwโฆ
While ex-ante screening and static price caps are global standards for mitigating price volatility, Singapore's electricity market employs a unique dual-defense mechanism integrating vesting contractsโฆ
Machine learning with artificial neural networks (ANNs), provides solutions for the growing complexity of modern communication systems. This complexity, however, increases power consumption, making thโฆ
This paper introduces a novel framework for robotic vision-based navigation that integrates Hybrid Neural Networks (HNNs) with Spiking Neural Network (SNN)-based filtering to enhance situational awareโฆ
The incorporation of advanced control algorithms into prosthetic hands significantly enhances their ability to replicate the intricate motions of a human hand. This work introduces a model-based contrโฆ
Most current assessments use ex post proxies that miss uncertainty and fail to consistently capture the rapid change in bitcoin mining. We introduce a unified, ex ante statistical model that derives eโฆ
The integration of Unmanned Aerial Vehicles (UAVs) and Unmanned Ground Vehicles (UGVs) is increasingly central to the development of intelligent autonomous systems for applications such as search and โฆ
Integrating autonomous mobile robots into human environments requires human-like decision-making and energy-efficient, event-based computation. Despite progress, neuromorphic methods are rarely applieโฆ
Soft computing tools emerged as most reliable alternatives of traditional regression and statistical methods. In recent times, these tools can predict the optimum material compositions, mechanical andโฆ
We present an end-to-end pipeline for deploying reinforcement learning (RL) trained Artificial Neural Networks (ANNs) on neuromorphic hardware by converting them into spiking Sigma-Delta Neural Networโฆ
Energy-efficient and high-performance motor control remains a critical challenge in robotics, particularly for high-dimensional continuous control tasks with limited onboard resources. While Deep Reinโฆ
This article presents a study on the application of artificial neural networks (ANNs) for maximum power point tracking (MPPT) in photovoltaic (PV) systems using low-cost pyranometer sensors. The propoโฆ
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