paper-with-me

홈 › Papers

Maximum Likelihood Estimation Based Complex-Valued Robust Chinese Remainder Theorem and Its Fast Algorithm

2025-03-24 · Xiaoping Li, Shiyang Sun, Qunying Liao, Xiang-Gen Xia

Recently, a multi-channel self-reset analog-to-digital converter (ADC) system with complex-valued moduli has been proposed. This system enables the recovery of high dynamic range complex-valued bandlimited signals at low sampling rates via the Chinese remainder theorem (CRT). In this paper, we investigate complex-valued CRT (C-CRT) with erroneous remainders, where the errors follow wrapped complex Gaussian distributions. Based on the existing real-valued CRT utilizing maximum likelihood estimation (MLE), we propose a fast MLE-based C-CRT (MLE C-CRT). The proposed algorithm requires only $2L$ searches to obtain the optimal estimate of the common remainder, where $L$ is the number of moduli. Once the common remainder is estimated, the complex number can be determined using the C-CRT. Furthermore, we obtain a necessary and sufficient condition for the fast MLE C-CRT to achieve robust estimation. Finally, we apply the proposed algorithm to ADCs. The results demonstrate that the proposed algorithm outperforms the existing methods.

📄 PDF Abstract BibTeX arXiv:2503.18625

Code (0)

등록된 구현이 없습니다.

Similar Papers 제목 키워드 기반

Estimation of Complex Valued Laplacian Matrices for Topology Identification in Power Systems

2023-08-07 · Morad Halihal, Tirza Routtenberg, H. Vincent Poor

In this paper, we investigate the problem of estimating a complex-valued Laplacian matrix with a focus on its application in the estimation of admittance matrices in power systems. The proposed approach is based on a con…

The Cramer-Rao Bound for Signal Parameter Estimation from Quantized Data

2022-09-27 · Petre Stoica, Xiaolei Shang, Yuanbo Cheng

Several current ultra-wide band applications, such as millimeter wave radar and communication systems, require high sampling rates and therefore expensive and energy-hungry analogto-digital converters (ADCs). In applicat…

parameter estimationQuantization

C-SURE: Shrinkage Estimator and Prototype Classifier for Complex-Valued Deep Learning

2020-06-22 · Yifei Xing, Rudrasis Chakraborty, Minxuan Duan, Stella Yu

The James-Stein (JS) shrinkage estimator is a biased estimator that captures the mean of Gaussian random vectors.While it has a desirable statistical property of dominance over the maximum likelihood estimator (MLE) in t…

Detecting Label Noise via Leave-One-Out Cross-Validation

2021-03-21 · Yu-Hang Tang, Yuanran Zhu, Wibe A. de Jong

We present a simple algorithm for identifying and correcting real-valued noisy labels from a mixture of clean and corrupted sample points using Gaussian process regression. A heteroscedastic noise model is employed, in w…

GPRregression

Probabilistic Models for High-Order Projective Dependency Parsing

2015-02-14 · Xuezhe Ma, Hai Zhao

This paper presents generalized probabilistic models for high-order projective dependency parsing and an algorithmic framework for learning these statistical models involving dependency trees. Partition functions and mar…

Dependency Parsingparameter estimationVocal Bursts Intensity Prediction