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In this paper, we discuss application of iterative Stochastic Optimization routines to the problem of sparse signal recovery from noisy observation. Using Stochastic Mirror Descent algorithm as a building block, we develop a multistage…

Machine Learning · Statistics 2022-03-31 Anatoli Juditsky , Andrei Kulunchakov , Hlib Tsyntseus

Source localization and spectral estimation are among the most fundamental problems in statistical and array signal processing. Methods which rely on the orthogonality of the signal and noise subspaces, such as Pisarenko's method, MUSIC,…

Information Theory · Computer Science 2019-04-16 Matthew W. Morency , Sergiy A. Vorobyov , Geert Leus

Using a Bayesian approach, we consider the problem of recovering sparse signals under additive sparse and dense noise. Typically, sparse noise models outliers, impulse bursts or data loss. To handle sparse noise, existing methods…

Machine Learning · Statistics 2015-01-13 Martin Sundin , Saikat Chatterjee , Magnus Jansson

The source separation-based speech enhancement problem with multiple beamforming in reverberant indoor environments is addressed in this paper. We propose that more generic solutions should cope with time-varying dynamic scenarios with…

Audio and Speech Processing · Electrical Eng. & Systems 2020-11-05 Alejandro Díaz , Diego Pincheira , Rodrigo Mahu , Nestor Becerra Yoma

Waves from a sparse set of source hidden in additive noise are observed by a sensor array. We treat the estimation of the sparse set of sources as a generalized complex-valued LASSO problem. The corresponding dual problem is formulated and…

Statistics Theory · Mathematics 2015-09-03 Christoph F. Mecklenbräuker , Peter Gerstoft , Erich Zöchmann

Sparse modeling is one of the efficient techniques for imaging that allows recovering lost information. In this paper, we present a novel iterative phase-retrieval algorithm using a sparse representation of the object amplitude and phase.…

Computer Vision and Pattern Recognition · Computer Science 2011-08-17 Artem Migukin , Vladimir Katkovnik , Jaakko Astola

We introduce the sparse direct sampling method (DSM) to estimate properties of a region from signals that probe the region. We demonstrate the sparse-DSM on two separate problems: estimating both the angle-of-arrival of a radio wave…

Analysis of PDEs · Mathematics 2020-10-19 Isaac Harris , Jacob D Rezac

A dictionary learning based audio source classification algorithm is proposed to classify a sample audio signal as one amongst a finite set of different audio sources. Cosine similarity measure is used to select the atoms during dictionary…

Sound · Computer Science 2015-10-28 K V Vijay Girish , T V Ananthapadmanabha , A G Ramakrishnan

Reverberations are unavoidable in enclosures, resulting in reduced intelligibility for hearing impaired and non native listeners and even for the normal hearing listeners in noisy circumstances. It also degrades the performance of machine…

Audio and Speech Processing · Electrical Eng. & Systems 2022-08-11 Sania Gul , Muhammad Salman Khan , Syed Waqar Shah

Almost all known image reconstruction algorithms for photoacoustic and thermoacoustic tomography assume that the acoustic waves leave the region of interest after a finite time. This assumption is reasonable if the reflections from the…

Analysis of PDEs · Mathematics 2015-06-16 L. Kunyansky , B. Holman , B. T. Cox

The paper shows the potential of sparsity-based methods in restoring quantized signals. Following up on the study of Brauer et al. (IEEE ICASSP 2016), we significantly extend the range of the evaluation scenarios: we introduce the analysis…

Signal Processing · Electrical Eng. & Systems 2020-08-13 Pavel Záviška , Pavel Rajmic

Conventional sparse phase retrieval schemes can recover sparse signals from the magnitude of linear measurements only up to a global phase ambiguity. This work proposes a novel approach that instead utilizes the magnitude of affine…

Information Theory · Computer Science 2021-05-25 Ming-Hsun Yang , Y. -W. Peter Hong , Jwo-Yuh Wu

In this paper we study the reconstruction of binary sparse signals from partial random circulant measurements. We show that the reconstruction via the least-squares algorithm is as good as the reconstruction via the usually used program…

Information Theory · Computer Science 2020-06-29 Sandra Keiper

It is known that sparse recovery is possible if the number of measurements is in the order of the sparsity, but the corresponding decoders either lack polynomial decoding time or robustness to noise. Commonly, decoders that rely on a null…

Information Theory · Computer Science 2024-09-04 Hendrik Bernd Zarucha , Peter Jung

Room geometry inference algorithms rely on the localization of acoustic reflectors to identify boundary surfaces of an enclosure. Rooms with highly absorptive walls or walls at large distances from the measurement setup pose challenges for…

Audio and Speech Processing · Electrical Eng. & Systems 2024-02-12 H. Nazim Bicer , Cagdas Tuna , Andreas Walther , Emanuël A. P. Habets

Knowing the geometry of a space is desirable for many applications, e.g. sound source localization, sound field reproduction or auralization. In circumstances where only acoustic signals can be obtained, estimating the geometry of a room is…

Sound · Computer Science 2019-07-03 Linh Nguyen , Jaime Valls Miro , Xiaojun Qiu

Music performances, characterized by dense and continuous audio as well as seamless audio-visual integration, present unique challenges for multimodal scene understanding and reasoning. Recent Music Performance Audio-Visual Question…

Sound · Computer Science 2025-06-03 Xingjian Diao , Tianzhen Yang , Chunhui Zhang , Weiyi Wu , Ming Cheng , Jiang Gui

The reproduction of acoustics is an important aspect of the preservation of cultural heritage. A common approach is to capture an impulse response in a hall and auralize it by convolving an input signal with the measured reverberant…

Audio and Speech Processing · Electrical Eng. & Systems 2024-10-28 Benoit Alary , Vesa Välimäki

We consider the problem of simultaneous reduction of acoustic echo, reverberation and noise. In real scenarios, these distortion sources may occur simultaneously and reducing them implies combining the corresponding distortion-specific…

Sound · Computer Science 2020-07-28 Guillaume Carbajal , Romain Serizel , Emmanuel Vincent , Eric Humbert

We describe a new method for estimating the direction of sound in a reverberant environment from basic principles of sound propagation. The method utilizes SNR-adaptive features from time-delay and energy of the directional components after…

Sound · Computer Science 2024-07-16 Mohamed F. Mansour