论文标题
一种用于实时波形拟合的递归方法，背景噪声排斥
A Recursive Method for Real-Time Waveform Fitting with Background Noise Rejection
论文作者
论文摘要
我们在这里提出了一种用于开发高通量算法的技术，以拟合模板脉冲形状的组合，同时减去参数化的背景噪声。通过沿着定期采样的波形迹线卷动最小二乘拟合设计矩阵的伪线，可以实时确定每个基函数的拟合参数的时间演变。我们使用分段多项式近似这些滑动线性拟合响应函数，并开发出在高样本量结果数据采集系统中实现的FPGA友好算法。这是一个可靠的通用滤波器，与为能量校准/分辨率优化的常见过滤器进行了很好的比较，即使存在明显的噪声组件，也可以优化定时性能的过滤器。
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.
