Sparse Representation of Feedback Filters in Delta-Sigma Modulators

被引：1

作者：

Nagahara, Masaaki ^{[1
]}

Yamamoto, Yutaka ^{[2
]}

机构：

[1] Univ Kitakyushu, Hibikino 1-1, Fukuoka 8080135, Japan

[2] Kyoto Univ, Sakyo Ku, Yoshida Honmachi, Kyoto 6068501, Japan

来源：

IFAC PAPERSONLINE | 2020年 / 53卷 / 02期

关键词：

Delta-sigma modulators; signal processing; quantization; sparse representation; convex optimization; H-infinity optimization; generalized KYP lemma; OPTIMIZATION; DESIGN;

D O I：

10.1016/j.ifacol.2020.12.320

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

In this paper, we propose sparse representation of FIR (Finite Impulse Response) feedback filters in delta-sigma modulators. The filter has a sparse structure, that is, only a few coefficients are non-zero, that stabilizes the feedback modulator, and minimizes the maximum magnitude of the noise transfer function at low frequencies. The optimization is described as an l(1) minimization with linear matrix inequalities (LMIs), based on the generalized KYP (Kalman-Yakubovich-Popov) lemma. A design example is shown to illustrate the effectiveness of the proposed method. Copyright (C) 2020 The Authors.

引用

页码：512 / 517

页数：6

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