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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
A reconfigurable non-linear active metasurface for cohere...
Pouria Sanjari, Firooz Aflatouni · 2024-11-15 · via eess.SP updates on arXiv.org

Metasurfaces can manipulate the amplitude and phase of electromagnetic waves, offering applications ranging from antenna design and cloaking to imaging and communication. Additionally, temporal, and non-linear metasurfaces have the potential to adjust the frequency of impinging waves, driving advancements in frequency conversion, sensing, and quantum systems. Here, we report the demonstration of a non-linear active electronic-photonic metasurface that transfers information from an impinging optical wave to a millimeter-wave (mm-wave) beam. The proof-of-concept metasurface is designed to radiate a steerable 28GHz beam when illuminated with an optical wave at 193THz and consists of optically synchronized electronic-photonic chips tiled on a printed circuit board containing a microstrip patch antenna array. Input light, modulated with a data-encoded mm-wave carrier, is coupled into electronic-photonic chips using microlenses. Within each chip, the mm-wave signal is detected, phase-adjusted, amplified, and routed to an off-chip antenna. Beam-steering over a range of 60$^{\circ}$ in elevation and azimuth and data transmission at 2Gb/s over a fiber-wireless link is demonstrated. Free-space optical synchronization can significantly reduce the complexity of large-scale metasurfaces composed of non-uniform or randomly placed elements, is compatible with scalable architectures, and facilitates data transfer and mm-wave beam shaping, allowing for large-scale high-bandwidth and energy-efficient links with reduced complexity for the next generation communication, computation, sensing and quantum systems.