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Discrete-Time Crossing-Point Estimation for Switching Power Converters.

机译:开关电源转换器的离散时间交叉点估计。

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摘要

In a number of electrical engineering problems, so-called "crossing points" -- the instants at which two continuous-time signals cross each other -- are of interest. Often, particularly in applications using a Digital Signal Processor (DSP), only periodic samples along with a partial statistical characterization of the signals are available. In this situation, we are faced with the following problem: Given limited information about these signals, how can we efficiently and accurately estimate their crossing points?;We consider estimating the crossing points of a known function and a Gaussian random process, given uniformly-spaced, noisy samples of the random process for which the second-order statistics are assumed to be known. We derive the Maximum A-Posteriori (MAP) estimator, along with a Minimum Mean-Squared Error (MMSE) estimator which we show to be a computationally efficient approximation to the MAP estimator.;We also derive the Cramer-Rao bound (CRB) on estimator variance for the problem, which allows practical estimators to be evaluated against a best-case performance limit. We investigate several comparison estimators chosen from the literature. The structure of the MMSE estimator and comparison estimators is shown to be very similar, making the difference in computational expense between each technique largely dependent on the cost of evaluating various (generally non-linear) functions.;Simulations for both Pulse-Width and Click Modulation scenarios show the MMSE estimator performs very near to the Cramer-Rao bound and outperforms the alternative estimators selected from the literature.;For example, an audio amplifier typically receives its input from a digital source decoded into regular samples (e.g. from MP3, DVD, or CD audio), or obtained from a continuous-time signal using an analog-to-digital converter (ADC). In a switching amplifier based on Pulse-Width Modulation (PWM) or Click Modulation (CM), a signal derived from the sampled audio is compared against a deterministic reference waveform; the crossing points of these signals control a switching power stage. Crossing-point estimates must be accurate in order to preserve audio quality. They must also be simple to calculate, in order to minimize processing requirements and delays.
机译:在许多电气工程问题中,有趣的是所谓的“交叉点”(两个连续时间信号彼此交叉的瞬间)。通常,尤其是在使用数字信号处理器(DSP)的应用中,只有周期性采样以及信号的部分统计特性可用。在这种情况下,我们面临以下问题:在这些信号的信息有限的情况下,我们如何才能有效,准确地估计其交叉点?我们考虑对已知函数和高斯随机过程的交叉点进行估计,并给出以下结论:假定二阶统计量已知的随机过程的有间隔噪声样本。我们得出最大A后验(MAP)估计量,以及最小均方误差(MMSE)估计量,我们证明这是对MAP估计量的有效计算近似;我们还得出了Cramer-Rao界(CRB)问题的估计变量方差,这使得可以根据最佳情况的性能极限来评估实际的估计量。我们调查了从文献中选择的几种比较估计量。 MMSE估计器和比较估计器的结构非常相似,因此每种技术之间的计算费用差异在很大程度上取决于评估各种(通常为非线性)函数的成本。调制方案显示MMSE估计器的性能非常接近Cramer-Rao边界,并且胜过了从文献中选择的其他估计器。例如,音频放大器通常从数字源接收其输入,该数字源被解码为常规样本(例如,从MP3,DVD接收)或CD音频),或使用模数转换器(ADC)从连续时间信号获得。在基于脉宽调制(PWM)或喀嗒调制(CM)的开关放大器中,将从采样音频中得出的信号与确定性参考波形进行比较;这些信号的交叉点控制开关功率级。交叉点估计必须准确才能保持音频质量。它们还必须易于计算,以最大程度地减少处理要求和延迟。

著录项

  • 作者

    Smecher, Graeme.;

  • 作者单位

    McGill University (Canada).;

  • 授予单位 McGill University (Canada).;
  • 学科 Engineering Electronics and Electrical.
  • 学位 M.Eng.
  • 年度 2009
  • 页码 80 p.
  • 总页数 80
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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