2020/12/10 by Aaron Jezghani, Jezghani, A. P., L. J. Broussard +3
Computer Science · #FOS: Electrical engineering #FOS: Physical sciences #Image and Signal Denoising Methods #Instrumentation and Detectors (physics.ins-det) #Nuclear Experiment (nucl-ex) #Signal Processing (eess.SP) #Speech and Audio Processing #Target Tracking and Data Fusion in Sensor Networks #electronic engineering #information engineering
paper · pdf · doi:10.48550/arxiv.2012.05937
openalex publication_date 2020/12/10 · openalex created_date 2020/12/21 · openalex updated_date 2026/07/28
We present here a technique for developing a high-throughput algorithm to fit a combination of template pulse shapes while simultaneously subtracting parameterized background noise. By convolving the psuedoinverse of the least-squares fit design matrix along a regularly sampled waveform trace, the time evolution of the fit parameters for each basis function can be determined in real-time. We approximate these sliding linear fit response functions using piecewise polynomials, and develop an FPGA-friendly algorithm to be implemented in high sample-rate data acquisition systems. This is a robust universal filter that compares well to common filters optimized for energy calibration/resolution, as well as filters optimized for timing performance, even when significant noise components are present.