Zobrazeno 1 - 10
of 76
pro vyhledávání: '"Alexei Novikov"'
Autor:
Mykola Lavreniuk, Alexei Novikov
Publikováno v:
Sistemnì Doslìdženâ ta Informacìjnì Tehnologìï, Iss 1 (2018)
З появою у вільному доступі великих обсягів супутникових даних дедалі більшої актуальності набуває розвиток методів машинного навчанн
Externí odkaz:
https://doaj.org/article/346ba5737dc540eba00e2fec01ed41e6
Publikováno v:
bioRxiv
In metagenomics, the study of environmentally associated microbial communities from their sampled DNA, one of the most fundamental computational tasks is that of determining which genomes from a reference database are present or absent in a given sam
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2961822f37eb31b199c91c41a593e9ce
https://europepmc.org/articles/PMC10153212/
https://europepmc.org/articles/PMC10153212/
Autor:
Stephen White, Alexei Novikov
Publikováno v:
IEEE Transactions on Signal Processing. 69:4403-4415
We consider the sparse phase retrieval problem of recovering a sparse signal $\mathbf {x}$ in $\mathbb {R}^d$ from intensity-only measurements in dimension $d \geq 2$ . Sparse phase retrieval can often be equivalently formulated as the problem of rec
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::903ef4fb4edb7e7e6174f5d27b5b851c
https://doi.org/10.1109/tsp.2021.3096796
https://doi.org/10.1109/tsp.2021.3096796
Publikováno v:
Proceedings of the National Academy of Sciences of the United States of America
Proceedings of the National Academy of Sciences of the United States of America, vol 117, iss 21
e-Archivo. Repositorio Institucional de la Universidad Carlos III de Madrid
instname
e-Archivo: Repositorio Institucional de la Universidad Carlos III de Madrid
Universidad Carlos III de Madrid (UC3M)
Proceedings of the National Academy of Sciences of the United States of America, vol 117, iss 21
e-Archivo. Repositorio Institucional de la Universidad Carlos III de Madrid
instname
e-Archivo: Repositorio Institucional de la Universidad Carlos III de Madrid
Universidad Carlos III de Madrid (UC3M)
Significance The ability to detect sparse signals from noisy, high-dimensional data is a top priority in modern science and engineering. For optimal results, current approaches need to tune parameters that depend on the level of noise, which is often
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::67c6e6faf8abcaa5e3786e1186245b43
http://europepmc.org/articles/PMC7260980
http://europepmc.org/articles/PMC7260980
We present an algorithm for coherent diffractive imaging with phaseless measurements. It treats the forward model as a combination of coherent and incoherent waves. The algorithm reconstructs absorption and phase contrast that quantifies the attenuat
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3c553a0a153e96ec61ba7c3da4787704
Publikováno v:
2021 IEEE Conference on Antenna Measurements & Applications (CAMA).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::20d79aab985669207ce43557ae66fe60
https://doi.org/10.1109/cama49227.2021.9703482
https://doi.org/10.1109/cama49227.2021.9703482
Publikováno v:
Communications on Pure and Applied Mathematics. 73:1453-1489
We study the following control problem. Fish with bounded aquatic locomotion speed swims in fast waters. Can the fish, under reasonable assumptions, get to a desired destination? It can, even if the flow is time-dependent. Moreover, given a prescribe
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d67a00ea39cdb1b7c71de8dc07f36cfe
https://doi.org/10.1002/cpa.21878
https://doi.org/10.1002/cpa.21878
Publikováno v:
e-Archivo. Repositorio Institucional de la Universidad Carlos III de Madrid
instname
instname
We present a holographic imaging approach for the case in which a single source-detector pair is used to scan a sample. The source-detector pair collects intensity-only data at different frequencies and positions. By using an appropriate illumination
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::61a12b50d34c3dba4f17a59bfbc8e853
https://hdl.handle.net/10016/32511
https://hdl.handle.net/10016/32511
We present a novel approach for recovering a sparse signal from quadratic measurements corresponding to a rank-one tensorization of the data vector. Such quadratic measurements, referred to as interferometric or cross-correlated data, naturally arise
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::77b32bc0d59323824bb87c81fbbd40e0