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eess.SP updates on arXiv.org

ECG-biometrics-bench: A Unified Framework for Reproducible Benchmarking of ECG Biometrics Physiology-Aware Masked Cross-Modal Reconstruction for Biosignal Representation Learning Towards Improving Speaker Distance Estimation through Generative Impulse Response Augmentation Federated Learning with Hypergradient-based Online Update of Aggregation Weights Soft Graph Diffusion Transformer for MIMO Detection SPLICE: Latent Diffusion over JEPA Embeddings for Conformal Time-Series Inpainting Sequential Inference for Gaussian Processes: A Signal Processing Perspective Statistical Channel Fingerprint Construction for Massive MIMO: A Unified Tensor Learning Framework Recent Advances in mm-Wave and Sub-THz/THz Oscillators for FutureG Technologies Cross-Subject Generalization for EEG Decoding: A Survey of Deep Learning Methods Super-resolution Multi-signal Direction-of-Arrival Estimation by Hankel-structured Sensing and Decomposition Hankel and Toeplitz Rank-1 Decomposition of Arbitrary Matrices with Applications to Signal Direction-of-Arrival Estimation Adaptive Transform Coding for Semantic Compression EdgeSpike: Spiking Neural Networks for Low-Power Autonomous Sensing in Edge IoT Architectures Sparse Graph Learning from Sparse Data via Fiedler Number Maximization A Deep Learning Model for Battery State Prediction towards Intelligent Energy Management Transfer Learning for Tonal Noise Prediction in VRF Units Using Thermodynamic and Vibration Signals EVT-Based Generative AI for Tail-Aware Channel Estimation Monitoring exposure-length variations in submarine power cables using distributed fiber-optic sensing BandRouteNet: An Adaptive Band Routing Neural Network for EEG Artifact Removal Phase-Separated Complex Hilbert PCA on Markerless 3D Pose Estimation Data: A Global Phase Network and Its Extension to a Continuous Field on the Body Surface Selective Correlation Based Knowledge Distillation for Ground Reaction Force Estimation Deep Learning-Enabled Dissolved Oxygen Sensing in Biofouling Environments for Ocean Monitoring Speech Enhancement Based on Drifting Models Robust and Clinically Reliable EEG Biomarkers: A Cross Population Framework for Generalizable Parkinson's Disease Detection An AI-Based Supervisory Measurement Integrity Validation Layer for Cyber-Resilient AC/DC Protection in Inverter-Based Microgrids Explainable AI in Speaker Recognition -- Making Latent Representations Understandable Time-Localized Parametric Decomposition of Respiratory Airflow for Sub-Breath Analysis NAKUL-Med: Spectral-Graph State Space Models with Dynamics Kernels for Medical Signals An Algorithm for On-Sensor Agnostic Detection of Changes in Human Activity for Ultra-Low-Power Applications
FEM-Based Dispersion and Mode Analysis of Rectangular, Ci...
[Submitted on 9 Jun 2026] · 2026-06-24 · via eess.SP updates on arXiv.org

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Abstract:This paper presents a two-dimensional finite element method (FEM) solver for computing modal field distributions and dispersion characteristics of hollow metallic waveguides. To solve the waveguide problem, the source-free frequency-domain Maxwell equations are reduced to scalar Helmholtz eigenvalue formulations evaluated over the waveguide's transverse cross section. The computational method determines both transverse electric (TE) and transverse magnetic (TM) mode families by enforcing perfectly electrically conducting (PEC) boundary conditions. The framework is initially validated against analytical benchmarks using empty rectangular and circular waveguides, demonstrating high accuracy in computing cutoff wavenumbers, dispersion curves, and field maps for the first three unique modes. After validation, the solver is applied to analyze single-ridged and double-ridged waveguides. The numerical results demonstrate that introducing metallic ridges successfully redistributes the modal fields and significantly lowers the cutoff frequency of the dominant mode relative to empty rectangular guides. Ultimately, this work confirms that the generalized eigenvalue FEM formulation is a robust and adaptable tool for analyzing complex waveguide geometries where exact analytical solutions are unavailable.

Submission history

From: Sabrina Saima [view email]
[v1] Tue, 9 Jun 2026 16:01:43 UTC (880 KB)