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Optimal FIR Filter Design based on Curve Fitting Approximation for Uncertain 2–1 Sigma–Delta Modulator

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Abstract

Uncertain components in the integrators of 2–1 Sigma–Delta modulators cannot eliminate the first stage quantization noise completely, and the signal-to-noise ratio in analogue-to-digital converters is not reduced perfectly either. In order to solve the matching problem, older filter designs based on convex optimization are mathematically complicated, computationally intensive and not so efficient in application. In this paper, we propose a design method based on curve fitting approximation for uncertain linearized model of the modulator which is simple in principle and practical in application. Simulation results show that the optimal filter has better performance on multiple validations when compared to other modulator filters.

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Acknowledgement

This work is supported by the Fundamental Research Funds for the Central Universities of China (Project No. N120304004) and China Postdoctoral Science Foundation (Project No. 2013M530937).

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Authors and Affiliations

  1. School of Information Science and Engineering, Northeastern University, Shenyang, 110004, China

    Jun Peng, Jianhui Wang & Shuai Tan

  2. Electrical and Computer Engineering, Purdue University, West Lafayetee, IN, 47906, US

    Jun Peng

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  1. Jun Peng
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  2. Jianhui Wang
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  3. Shuai Tan
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Correspondence to Shuai Tan.

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Peng, J., Wang, J. & Tan, S. Optimal FIR Filter Design based on Curve Fitting Approximation for Uncertain 2–1 Sigma–Delta Modulator. Circuits Syst Signal Process 33, 885–894 (2014). https://doi.org/10.1007/s00034-013-9671-7

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  • DOI: https://doi.org/10.1007/s00034-013-9671-7

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