Zobrazeno 1 - 10
of 235
pro vyhledávání: '"Ronen Talmon"'
Publikováno v:
Nature Communications, Vol 15, Iss 1, Pp 1-10 (2024)
Abstract Avalanche sources describe rapid and local events that govern deformation processes in various materials. The fundamental differences between an avalanche source and its associated measured acoustic emission (AE) signal are encoded in the ac
Externí odkaz:
https://doaj.org/article/f25c305a6e5545f2a2b53070b603687a
Autor:
Nir Habouba, Ronen Talmon, Dror Kraus, Rola Farah, Alan Apter, Tamar Steinberg, Rupa Radhakrishnan, Daniel Barazany, Tzipi Horowitz-Kraus
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-20 (2024)
Abstract Neural fingerprinting is a method to identify individuals from a group of people. Here, we established a new connectome-based identification model and used diffusion maps to show that biological parent–child couples share functional connec
Externí odkaz:
https://doaj.org/article/6212566515a6476f940e1e1d39ff573a
Publikováno v:
EURASIP Journal on Audio, Speech, and Music Processing, Vol 2021, Iss 1, Pp 1-16 (2021)
Abstract Two novel methods for speaker separation of multi-microphone recordings that can also detect speakers with infrequent activity are presented. The proposed methods are based on a statistical model of the probability of activity of the speaker
Externí odkaz:
https://doaj.org/article/47c121c17e604358be70bba359acd35d
Autor:
Ya-Wei Eileen Lin, Tal Shnitzer, Ronen Talmon, Franz Villarroel-Espindola, Shruti Desai, Kurt Schalper, Yuval Kluger
Publikováno v:
PLoS Computational Biology, Vol 17, Iss 3, p e1008741 (2021)
Imaging Mass Cytometry (IMC) combines laser ablation and mass spectrometry to quantitate metal-conjugated primary antibodies incubated in intact tumor tissue slides. This strategy allows spatially-resolved multiplexing of dozens of simultaneous prote
Externí odkaz:
https://doaj.org/article/1b79d21b07f74f38847553da6ed37362
Autor:
Almog Lahav, Ronen Talmon
Publikováno v:
IEEE Transactions on Signal Processing. :1-15
Autor:
Felix P. Kemeth, Sindre W. Haugland, Felix Dietrich, Tom Bertalan, Kevin Hohlein, Qianxiao Li, Erik M. Bollt, Ronen Talmon, Katharina Krischer, Ioannis G. Kevrekidis
Publikováno v:
IEEE Access, Vol 6, Pp 77402-77413 (2018)
Manifold-learning techniques are routinely used in mining complex spatiotemporal data to extract useful, parsimonious data representations/parametrizations; these are, in turn, useful in nonlinear model identification tasks. We focus here on the case
Externí odkaz:
https://doaj.org/article/9d795c384df047b186d273cf5d16fed1
Publikováno v:
Information and Inference: A Journal of the IMA. 11:1173-1202
Motivated by establishing theoretical foundations for various manifold learning algorithms, we study the problem of Mahalanobis distance (MD) and the associated precision matrix estimation from high-dimensional noisy data. By relying on recent transf
Publikováno v:
Chaos (Woodbury, N.Y.). 32(8)
We address a three-tier numerical framework based on nonlinear manifold learning for the forecasting of high-dimensional time series, relaxing the “curse of dimensionality” related to the training phase of surrogate/machine learning models. At th
During Deep Brain Stimulation(DBS) surgery for treating Parkinson's disease, one vital task is to detect a specific brain area called the Subthalamic Nucleus(STN) and a sub-territory within the STN called the Dorsolateral Oscillatory Region(DLOR). Ac
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c193ff6d72c4ea85565721123f7d004d
http://arxiv.org/abs/2208.10788
http://arxiv.org/abs/2208.10788
Publikováno v:
Foundations and Trends® in Signal Processing. 14:1-161