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State estimation or filtering serves as a fundamental task to enable intelligent decision-making in applications such as autonomous vehicles, robotics, healthcare monitoring, smart grids, intelligent transportation, and predictive…

Machine Learning · Computer Science 2025-06-16 Aamir Hussain Chughtai

We consider a least absolute deviation (LAD) approach to the robust phase retrieval problem that aims to recover a signal from its absolute measurements corrupted with sparse noise. To solve the resulting non-convex optimization problem, we…

Signal Processing · Electrical Eng. & Systems 2024-04-25 Seonho Kim , Kiryung Lee

We present a resource-efficient method based on repetitive weak measurements to directly measure the noise spectrum of a generic quantum environment that causes qubit phase decoherence. The weak measurement is induced by a Ramsey…

Quantum Physics · Physics 2026-01-27 Yuan-De Jin , Zheng-Fei Ye , Wen-Long Ma

The problem of covariance estimation for replicated surface-valued processes is examined from the functional data analysis perspective. Considerations of statistical and computational efficiency often compel the use of separability of the…

Methodology · Statistics 2021-10-25 Tomas Masak , Victor M. Panaretos

The reverberation time (T60) and the direct-to-reverberant ratio (DRR) are commonly used to characterize room acoustic environments. Both parameters can be measured from an acoustic impulse response (AIR) or using blind estimation methods…

Sound · Computer Science 2019-10-23 Nicholas J. Bryan

When measurements from dynamical systems are noisy, it is useful to have estimation algorithms that have low sensitivity to measurement noises and outliers. In the first set of results described in this paper we obtain optimal estimators…

Systems and Control · Electrical Eng. & Systems 2022-09-20 Krishan Mohan Nagpal

Modern time series are usually composed of multiple oscillatory components, with time-varying frequency and amplitude contaminated by noise. The signal processing mission is further challenged if each component has an oscillatory pattern,…

Signal Processing · Electrical Eng. & Systems 2021-10-04 Marcelo A. Colominas , Hau-Tieng Wu

Compressed Sensing suggests that the required number of samples for reconstructing a signal can be greatly reduced if it is sparse in a known discrete basis, yet many real-world signals are sparse in a continuous dictionary. One example is…

Information Theory · Computer Science 2015-07-24 Yuanxin Li , Yuejie Chi

This paper presents a complete description of noise-induced decay of a metastable state in a wide range of noise intensity. Recurrent formulas of exact moments of decay time valid for arbitrary noise intensity have been obtained. The…

adap-org · Physics 2007-05-23 Svetlana P. Nikitenkova , Andrey L. Pankratov

We present a method to remove unknown convolutive noise introduced to speech by reverberations of recording environments, utilizing some amount of training speech data from the reverberant environment, and any available non-reverberant…

Audio and Speech Processing · Electrical Eng. & Systems 2022-10-04 Samik Sadhu , Hynek Hermansky

We study an efficient dynamic blind source separation algorithm of convolutive sound mixtures based on updating statistical information in the frequency domain, andminimizing the support of time domain demixing filters by a weighted least…

Statistics Theory · Mathematics 2007-05-23 Jie Liu , Jack Xin , Yingyong Qi

We obtained a semi-analytical treatment obtaining estimators for the sample variance and variance of sample variance for the RTS noise. Our method suggests a way to experimentally determine the constants of capture and emission in the case…

Applied Physics · Physics 2022-01-27 Roberto da Silva , Gilson Wirth

Sparse linear regression methods such as Lasso require a tuning parameter that depends on the noise variance, which is typically unknown and difficult to estimate in practice. In the presence of heavy-tailed noise or adversarial outliers,…

Statistics Theory · Mathematics 2025-06-17 Takeyuki Sasai , Hironori Fujisawa

In this paper, we consider the problem of estimating finite rate of innovation (FRI) signals from noisy measurements, and specifically analyze the interaction between FRI techniques and the underlying sampling methods. We first obtain a…

Information Theory · Computer Science 2016-11-18 Zvika Ben-Haim , Tomer Michaeli , Yonina C. Eldar

Numerous biological and microscale systems exhibit synchronization in noisy environments. The theory of such noisy oscillators and their synchronization has been developed and experimentally demonstrated, but inferring the noise intensity…

Adaptation and Self-Organizing Systems · Physics 2025-01-09 Hisa-Aki Tanaka , Somei Suga , Akira Keida , Hiroya Nakao , Yutaka Jitsumatsu , István Z. Kiss

An efficient technique is introduced for model inference of complex nonlinear dynamical systems driven by noise. The technique does not require extensive global optimization, provides optimal compensation for noise-induced errors and is…

Data Analysis, Statistics and Probability · Physics 2007-05-23 V. N. Smelyanskiy , D. A. Timucin , A. Bandrivskyy , D. G. Luchinsky

How to efficiently utilize the temporal features is crucial, yet challenging, for video restoration. The temporal features usually contain various noisy and uncorrelated information, and they may interfere with the restoration of the…

Computer Vision and Pattern Recognition · Computer Science 2022-04-12 Cong Huang , Jiahao Li , Bin Li , Dong Liu , Yan Lu

We investigate robustness of probabilistic storage and retrieval device optimized for phase gates to noise. We use noisy input composed of convex combination of unitary channel with either depolarizing or dephasing channel. We find out that…

Quantum Physics · Physics 2022-11-30 Jaroslav Pavličko , Mário Ziman

This paper presents a simple and effective two-stage mesh denoising algorithm, where in the first stage, the face normal filtering is done by using the bilateral normal filtering in the robust statistics framework. Tukey's bi-weight…

Graphics · Computer Science 2017-11-22 Sunil Kumar Yadav , Ulrich Reitebuch , Konrad Polthier

In the realm of amateur radio, the effective classification of signals and the mitigation of noise play crucial roles in ensuring reliable communication. Traditional methods for signal classification and noise reduction often rely on manual…

Signal Processing · Electrical Eng. & Systems 2024-02-29 Jimi Sanchez