Results 41 to 50 of about 34,525 (261)

Sound field separation based on dictionary learning and sparse sampling

AIP Advances
Sound field separation techniques are an advancing tool for extracting a target sound field from a mixed sound field. However, the methods bear a high measurement cost due to the restriction of the sampling theorem.
Yuan Liu, Yongchang Li, Jinyu Zhao
doaj   +1 more source

Sound field separation with cross measurement surfaces. [PDF]

PLoS ONE, 2018
With conventional near-field acoustical holography, it is impossible to identify sound pressure when the coherent sound sources are located on the same side of the array.
Jin Mao, Jinfu Du
doaj   +1 more source

Investigation of Laser Ablation and Brush Pre‐Treatments for AlCu Cold Roll Bonding in Oxygen‐Free Conditions

Advanced Engineering Materials, EarlyView.
It is shown that laser ablation pretreatment under oxygen‐free conditions enables copper–aluminium bonding at significantly lower deformation degrees and improved properties compared to mechanical brushing. Laser ablation further increases interface contact area and induces favourable residual stress states and microstructural compatibility ...
Khemais Barienti, Finn‐Lennard Janthur, Selina Raumel, Sascha Jan Zimmermann, Sarah Seffer, René Gustus, Sebastian Herbst, Marc C. Wurz, Ludger Overmeyer, Wolfgang Maus‐Friedrichs, Hans Jürgen Maier, Florian Nürnberger   +11 more
wiley   +1 more source

Sound Localization and Speech Enhancement Algorithm Based on Dual-Microphone

Sensors, 2022
In order to simplify the complexity and reduce the cost of the microphone array, this paper proposes a dual-microphone based sound localization and speech enhancement algorithm.
Tao Tao, Hong Zheng, Jianfeng Yang, Zhongyuan Guo, Yiyang Zhang, Jiahui Ao, Yuao Chen, Weiting Lin, Xiao Tan   +8 more
doaj   +1 more source

Variational EM for binaural sound-source separation and localization [PDF]

2013 IEEE International Conference on Acoustics, Speech and Signal Processing, 2013
The sound-source separation and localization (SSL) problems are addressed within a unified formulation. Firstly, a mapping between white-noise source locations and binaural cues is estimated. Secondly, SSL is solved via Bayesian inversion of this mapping in the presence of multiple sparse-spectrum emitters (such as speech), noise and reverberations. We
Deleforge, Antoine, Forbes, Florence, Horaud, Radu   +2 more
openaire   +2 more sources

Characterization of Nitinol Produced by Laser Powder Bed Fusion for Mechanical Metamaterial Applications

Advanced Engineering Materials, EarlyView.
Stabilization of L‐PBF Ni50.7Ti49.3 under low‐cycle loading was investigated. Recoverable strain after cycling was dependent on the amount of applied load. Recovery ratio was 53.4% and 35.1% at intermediate and high load, respectively. The maximum total strain reached 10.3% at a high load of 1200 MPa.
Ondřej Červinek, Jakub Hurník, Miroslav Šmíd, Ondřej Zobač, Melanie Todt, Daniel Koutný   +5 more
wiley   +1 more source

Robot Audition and Computational Auditory Scene Analysis

Advanced Intelligent Systems, 2020
Robot audition aims at developing robot's ears that work in the real world, that is, machine listening of multiple sound sources. Its critical problem is noise.
Kazuhiro Nakadai, Hiroshi G. Okuno
doaj   +1 more source

Leveraging Sound Source Trajectories for Universal Sound Separation

IEEE Transactions on Audio, Speech and Language Processing
Existing methods utilizing spatial information for sound source separation require prior knowledge of the direction of arrival (DOA) of the source or utilize estimated but imprecise localization results, which impairs the separation performance, especially when the sound sources are moving.
Donghang Wu, Xihong Wu, Tianshu Qu
openaire   +2 more sources

Unleashing the Power of Machine Learning in Nanomedicine Formulation Development

Advanced Functional Materials, EarlyView.
A random forest machine learning model is able to make predictions on nanoparticle attributes of different nanomedicines (i.e. lipid nanoparticles, liposomes, or PLGA nanoparticles) based on microfluidic formulation parameters. Machine learning models are based on a database of nanoparticle formulations, and models are able to generate unique solutions
Thomas L. Moore, Cristiano Pesce, Antonietta Greco, Claudia Pisante, Greta Avancini, Valentina Di Francesco, Yosi Shamay, Paolo Decuzzi   +7 more
wiley   +1 more source

Non-negative tensor factorisation for sound source separation [PDF]

IEE Irish Signals and Systems Conference 2005, 2005
An algorithm for Non-negative Tensor Factorisation is introduced which extends current matrix factorisation techniques to deal with tensors. The effectiveness of the algorithm is then demonstrated through tests on synthetic data. The algorithm is then employed as a means of performing sound source separation on two channel mixtures, and the separation ...
Fitzgerald, Derry, Cranitch, Matt, Coyle, Eugene   +2 more
openaire   +3 more sources