一种抑制背景噪声的实时波形拟合递归方法
A Recursive Method for Real-Time Waveform Fitting with Background Noise Rejection
摘要：
我们在这里提出了一种技术，用于开发一个高通量的算法，以适应模板脉冲形状的组合，同时减去参数化的背景噪声。通过沿着规则采样的波形轨迹卷积最小二乘拟合设计矩阵的伪逆，可以实时确定每个基函数的拟合参数的时间演变。我们近似这些滑动线性拟合响应函数使用分段多项式，并开发了一个FPGA友好的算法，在高采样率数据采集系统中实现。这是一款鲁棒的通用滤波器，即使在存在显著噪声分量的情况下，也能与针对能量校准/分辨率进行优化的常见滤波器以及针对时序性能进行优化的滤波器相媲美。
英文摘要：
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.
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