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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
Optimization design of a micro-perforated panel absorber ...
Xiaoming Wang, Chen Liang, Yulin Mei · 2023-04-23 · via eess.SP updates on arXiv.org

In order to improve low-frequency characteristics of micro-perforated panel absorbers, sound absorption structures composed of micro-perforated panels and expansion chambers are design, and an optimization design method is constructed based on the transfer function model and the simulated annealing algorithm. First, a single-chamber structure composed of a micro-perforated panel and an expansion chamber is build, and the sound absorption curve is simulated by the finite element method. Second, for the sake of enlarging the continuous absorption bandwidth with absorption coefficients not less than 0.8, a three-chamber structure is designed, which has a sound absorption bandwidth of 1277Hz (27-1304Hz) covering 5.6 octave bands. Then, the transfer function model of the structure is established, and a series of theoretical formulae are derived to calculate the absorption coefficients. Subsequently, the sound absorption bandwidths calculated by the theoretical formulae and the finite element method are compared, and the relative error is 3.68%. Finally, an optimization design method is constructed by combining the transfer function model and the simulated annealing algorithm, where the optimization objective is to maximize the absorption bandwidth and the optimization variables are structural parameters of the three-chamber structure. The results show, after optimization, the three-chamber structure exhibits an excellent sound absorption performance, with a continuous bandwidth of 1591Hz (4-1595Hz), realizing 8.6 octave bands.