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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
Real-Time Interactive Hybrid Ocean: Spectrum-Consistent W...
Shengze Xue, Yu Ren, Jiacheng Hong, Run Ni, Shuangjiu Xiao, Deli · 2025-10-31 · via eess.SP updates on arXiv.org

Fast Fourier Transform-based (FFT) spectral oceans are widely adopted for their efficiency and large-scale realism, but they assume global stationarity and spatial homogeneity, making it difficult to represent non-uniform seas and near-field interactions (e.g., ships and floaters). In contrast, wave particles capture local wakes and ripples, yet are costly to maintain at scale and hard to match global spectral statistics.We present a real-time interactive hybrid ocean: a global FFT background coupled with local wave-particle (WP) patch regions around interactive objects, jointly driven under a unified set of spectral parameters and dispersion. At patch boundaries, particles are injected according to the same directional spectrum as the FFT, aligning the local frequency-direction distribution with the background and matching energy density, without disturbing the far field.Our approach introduces two main innovations: (1) Hybrid ocean representation. We couple a global FFT background with local WP patches under a unified spectrum, achieving large-scale spectral consistency while supporting localized wakes and ripples.(2) Frequency-bucketed implementation. We design a particle sampling and GPU-parallel synthesis scheme based on frequency buckets, which preserves spectral energy consistency and sustains real-time interactive performance.Together, these innovations enable a unified framework that delivers both large-scale spectral realism and fine-grained interactivity in real time.