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On Incremental Sigma-Delta Modulation With Optimal Filtering

机译:具有最佳滤波的增量Sigma-Delta调制

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The paper presents a quantization-theoretic framework for studying incremental sigma-delta (ΣΔ) data conversion systems. The framework makes it possible to efficiently compute the quantization intervals and hence the transfer function of the quantizer, and to determine the mean square error (MSE) and maximum error for the optimal and conventional linear filters for first and second order incremental ΣΔ modulators. The results show that the optimal filter can significantly outperform conventional linear filters in terms of both MSE and maximum error. The performance of conventional ΣΔ data converters is then compared to that of incremental ΣΔ with optimal filtering for ban-dlimited signals. It is shown that incremental ΣΔ can outperform the conventional approach in terms of signal-to-noise-and-distortion ratio. The framework is also used to provide a simpler and more intuitive derivation of the Zoomer algorithm.
机译:本文提出了一种用于研究增量sigma-delta(ΣΔ)数据转换系统的量化理论框架。该框架使得可以有效地计算量化间隔并因此计算量化器的传递函数,并确定用于一阶和二阶增量∑Δ调制器的最佳和常规线性滤波器的均方误差(MSE)和最大误差。结果表明,就MSE和最大误差而言,最佳滤波器可以明显优于常规线性滤波器。然后将常规ΣΔ数据转换器的性能与增量ΣΔ的性能进行比较,并针对禁令限制信号进行最佳滤波。结果表明,增量ΣΔ在信噪比和失真比方面可以优于传统方法。该框架还用于提供Zoomer算法的更简单,更直观的推导。

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