Theory and Algorithms for Pulse Signal Processing
Theory and Algorithms for Pulse Signal Processing
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DOI：
10.1109/tcsi.2020.2981318
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发表时间：
2018-12
期刊：
影响因子：
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通讯作者：
G. Nallathambi;J. Príncipe
中科院分区：
文献类型：
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作者：
G. Nallathambi;J. Príncipe
集成火转换器 (IFC) 将模拟信号转换为一串双相脉冲。脉冲序列具有以脉冲的时序和极性编码的信息。虽然已经表明可以从这些脉冲序列重建任何有限带宽模拟信号，并且误差尽可能小，但仍然需要基本信号处理技术来直接对脉冲序列进行操作而无需信号重建。在本文中，提出了使用模拟信号的脉冲序列表示在线执行模拟信号的加法、乘法和卷积运算的可行性。推导了使用施加最小限制的 IFC 脉冲序列执行信号处理的理论框架，并开发了运算符在线实现的算法。通过量化脉冲瞬时发生的变化来研究所提出算法的性能。通过重建脉冲序列的数字处理进行比较。此外，还以每秒小于 20 个 IFC 脉冲的稀疏数据速率和 0.16 ± 0.18 bpm 的心率绝对误差演示了噪声扣除和心电图信号相关相关特征表示的应用。
The integrate and fire converter (IFC) transforms an analog signal into a train of biphasic pulses. The pulse train has information encoded in the timing and polarity of pulses. While it has been shown that any finite bandwidth analog signal can be reconstructed from these pulse trains with an error as small as desired, there is a need for fundamental signal processing techniques to operate directly on pulse trains without signal reconstruction. In this paper, the feasibility of performing online the operations of addition, multiplication, and convolution of analog signals using their pulses train representations is presented. The theoretical framework to perform signal processing with IFC pulse trains imposing minimal restrictions is derived, and algorithms for online implementation of the operators is developed. The performance of the proposed algorithms is studied by quantifying the variations in instantaneous occurrence of pulses. Comparisons are performed with digital processing of reconstructed pulse trains. Moreover, an application of noise subtraction and representation of relevant features of interest in electrocardiogram signal is demonstrated with a sparse data rate of less than 20 IFC pulses per second, and an absolute error in heart rate of 0.16 ± 0.18 bpm.