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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
Application of deconvolution to recover frequency-domain ...
M. Mishra, J. Mattingly, R. M. Kolbas · 2019-02-23 · via eess.SP updates on arXiv.org

Multiplexing of radiation detectors reduces the number of readout channels, which in turn reduces the number of digitizer input channels for data acquisition. We recently demonstrated frequency domain multiplexing (FDM) of pulse mode radiation detectors using a resonator that converts the detector signal into a damped sinusoid by convolution. The detectors were given unique "tags" by the oscillation frequency of each resonator. The charge collected and the time-of-arrival of the detector pulse were estimated from the corresponding resonator output in the frequency domain. In this paper, we demonstrate a new method to recover the detector pulse from the damped sinusoidal output by deconvolution. Deconvolution converts the frequency-encoded detector signal back to the original detector pulse. We have developed a new prototype FDM system to multiplex organic scintillators based on convolution and deconvolution. Using the new prototype, the charge collected under the anode pulse can be estimated from the recovered pulse with an uncertainty of about 4.4 keVee (keV electron equivalent). The time-of-arrival can be estimated from the recovered pulse with an uncertainty of about 102 ps. We also used a CeBr3 inorganic scintillator to measure the Cs-137 gamma spectrum using the recovered pulses and found a standard deviation of 13.8 keV at 662 keV compared to a standard deviation of 13.5 keV when the original pulses were used. Coincidence measurements with Na-22 using the deconvolved pulses resulted in a timing uncertainty of 617 ps compared to an uncertainty of 603 ps using the original pulses. Pulse shape discrimination was also performed using Cf-252 source and EJ-309 organic scintillator pulses recovered by deconvolution. A figure of merit value of 1.08 was observed when the recovered pulses were used compared to 1.2 for the original pulses.