Electrical Eng. & Systems
While recent Large Language Model (LLM)-based Text-to-Speech (TTS) systems have achieved remarkable naturalness, they predominantly rely on implicit end-to-end generation paradigms, resulting in coarse-grained control. In scenarios…
This paper studies input-to-state stability (ISS) certification for data-driven Koopman learning control of unknown discrete-time nonlinear repetitive systems over finite trial horizons. Rather than proposing a new learning law, we certify…
Energy-efficient neuromorphic computing at the edge requires simulation tools that can capture the non-ideal behavior of mixed-signal spiking neural network (SNN) hardware while supporting system-level design exploration. This work presents…
Adaptive control learns the plant online; neural-operator control learns the control gains offline. We bring the two together for a class of nonlinear hyperbolic PDEs whose dynamics are governed by an unknown Volterra series of arbitrarily…
This paper systematically analyzes the relationships among the $dq$-domain, $\alpha\beta$-domain, and sequence-domain representations used in small-signal impedance modeling of voltage-source converters (VSCs). It is shown that the AC…
Accurate quantification of lung disease severity from chest imaging is critical for clinical decision-making and resource allocation. We propose a tri-modal deep learning framework, TMF-RSE (Tri-Modal Fusion with Regional Semantics and…
We evaluate joint probabilistic and geometric constellation shaping via reinforcement learning for complexity-constrained joint equalization and demodulation of direct detection optical signals. We demonstrate the proposed technique in a…
Microphone array-based passive acoustic monitoring is increasingly used for biodiversity sensing in forests. However, design and evaluation of array systems and configurations remains difficult since field recordings are costly, difficult…
Bending beams, characterized by their non diffracting and self-healing properties in the near field, offer a new approach to bypass blockage in terahertz (THz) wireless communication and sensing. However, the investigations of bend ing…
Voice anonymisation aims to protect speaker identity. Currently, its empirical privacy evaluation heavily relies on the Equal Error Rate (EER). Originally designed for biometric verification, EER aggregates scores globally, implicitly…
Pulse-echo speed-of-sound (SoS) imaging based on minute misalignments between consecutively acquired ultrasound images traditionally relies on images beamformed on Cartesian grids. Existing SoS imaging developments do not allow for…
Virtual admittance (VA) is widely used in cascaded voltage-control and current-control (VC-CC) grid-forming inverters (GFMIs) because it shapes the converter terminal behavior while preserving the current-regulation path required for…
There are some datasets of varying scales for audio classification (AC) applied to different tasks. However, annotated data is limited for most scenarios, such as domestic environments. To address this challenge, we propose an…
Industrial prediction and soft sensing depend on credible input measurements. In field deployment, a predictor may receive biased, delayed, stale, or derived measurements that still look plausible. Prediction can then fail before the…
The continuous monitoring of the physical downlink control channel (PDCCH) is a major source of energy consumption in fifth-generation (5G) Internet of thing device (IoT-D), since the UE has to blindly detect downlink control information…
In this paper, we propose a self-superheterodyne Rydberg uniform array receiver for satellite uplink communications, in which the Doppler shift naturally induced by satellite motion is exploited to generate the intermediate-frequency…
Few-shot Class-incremental Audio Classification (FCAC) aims to progressively recognize incremental classes with few tagged samples and meanwhile memorize base classes. To achieve satisfactory FCAC performance, the model needs to have high…
Efficient model order reduction for many-port resistor-capacitor (RC) networks is essential in post-layout circuit simulation. Existing high-accuracy elimination-based methods have certain limitations, such as fixed frequency points, large…
Next-generation space-air-ground-sea integrated networks (SAGSIN) impose unprecedented demands on advanced radio frequency (RF) receivers for full-spectrum agility, ultra-high sensitivity, and anti-jamming resilience, pushing conventional…
The concept of Digital Twin (DT) consists of a physical asset, a digital asset, and their bidirectional data exchange, differing the DT from concepts with lower level of integration. Availability of the bidirectional interconnection not…