Evaluation of a Modulo Sampling Hardware Prototype and Reconstruction Algorithms for High Dynamic Range Signals
This paper presents a novel modulo analog-to-digital converter (ADC) hardware prototype capable of sampling high dynamic range signals without saturation and evaluates the effectiveness of various reconstruction algorithms in recovering the original signal from the modulo samples.
1비트 폴딩 정보를 사용하는 모듈로 ADC를 위한 슬라이딩 DFT 기반 신호 복구
1비트 폴딩 정보를 갖춘 모듈로 ADC에서 슬라이딩 DFT 기반 신호 복구 방법을 사용하면 기존 ADC보다 오버샘플링 시스템에서 더 나은 MSE 성능을 얻을 수 있습니다.
基於矩陣束和中國剩餘定理的真次奈奎斯特方法實現超分辨率
本文提出了一種基於矩陣束和中國剩餘定理的真次奈奎斯特方法，用於提高高頻信號提取中的頻率分辨率和精度，並在模擬數據中驗證了其有效性。
超解像度を実現する真のサブナイキスト法に基づく行列ペンシル法と中国剰余定理の統合
本稿では、行列ペンシル法と中国剰余定理（CRT）を統合した新しい超解像度一般化固有値法を提案し、真のサブナイキストフレームワーク内で信号処理能力を高め、高周波信号抽出における周波数分解能と精度を向上させることを目指しています。
基於迭代收縮總變異演算法的一維訊號噪聲去除
本文介紹了一種基於總變異 (TV) 的迭代收縮演算法，用於去除一維訊號中的噪聲，並通過合成訊號的濾波測試，驗證了該演算法在不同噪聲水平和訊號類型下的有效性。
一次元信号におけるノイズ除去のための反復収縮全変動アルゴリズム
本稿では、一次元信号からノイズを除去する効果的な方法として、全変動フィルタリングに基づく反復収縮アルゴリズムを紹介し、その有効性を検証している。
Noise Removal in One-Dimensional Signals Using the Iterative Shrinkage Total Variation Algorithm: A Practical Exploration with Synthetic and Real-World Audio Data
Total Variation (TV) filtering, particularly the Iterative Shrinkage Algorithm, effectively removes noise from one-dimensional signals, as demonstrated through synthetic tests and real-world audio data, including the removal of vuvuzela noise.
Robust Multipath Signal Separation for Automotive Radar Interference Mitigation
A novel variational inference algorithm is proposed to jointly estimate the parameters of coherent radar echoes and non-coherent interference signals, enabling robust object detection and parameter estimation under mutual radar interference.
Oversampled Low Ambiguity Zone Sequences for Efficient Channel Estimation over Doubly Selective Channels
Oversampled low ambiguity zone (O-LAZ) sequences can be effectively used as pilot sequences for efficient channel estimation in doubly selective channels.
Efficient Sub-Nyquist Spectral Estimation of High-Dynamic-Range Signals Using Modulo Sampling
A novel sub-Nyquist spectral estimation method based on the Unlimited Sensing Framework (USF) can recover K sinusoids from only 6K + 4 modulo samples, independent of the sampling rate or folding threshold, enabling efficient high-dynamic-range signal acquisition.
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