Results 31 to 40 of about 122,061 (212)
Application of compressed sensing to the simulation of atomic systems
, 2012 Compressed sensing is a method that allows a significant reduction in the number of samples required for accurate measurements in many applications in experimental sciences and engineering.
A. Aspuru-Guzik +16 more
core +1 more source
Compressive Sensing with Optical Chaos [PDF]
Scientific Reports, 2016 AbstractCompressive sensing (CS) is a technique to sample a sparse signal below the Nyquist-Shannon limit, yet still enabling its reconstruction. As such, CS permits an extremely parsimonious way to store and transmit large and important classes of signals and images that would be far more data intensive should they be sampled following the ...
C. Y. Chang +6 more
openaire +5 more sources
Hyperspectral compressive wavefront sensing
High Power Laser Science and Engineering, 2023 Abstract Presented is a novel way to combine snapshot compressive imaging and lateral shearing interferometry in order to capture the spatio-spectral phase of an ultrashort laser pulse in a single shot. A deep unrolling algorithm is utilized for snapshot compressive imaging reconstruction due to its parameter efficiency and superior speed relative ...
Sunny Howard +4 more
openaire +4 more sources
Exploration of heterogeneity and recurrence signatures in hepatocellular carcinoma
Molecular Oncology, EarlyView.This study leveraged public datasets and integrative bioinformatic analysis to dissect malignant cell heterogeneity between relapsed and primary HCC, focusing on intercellular communication, differentiation status, metabolic activity, and transcriptomic profiles.
Wen‐Jing Wu +15 more
wiley +1 more source
Recursive Compressed Sensing [PDF]
, 2013 We introduce a recursive algorithm for performing compressed sensing on streaming data. The approach consists of a) recursive encoding, where we sample the input stream via overlapping windowing and make use of the previous measurement in obtaining the ...
Freris, Nikolaos M. +2 more
core +1 more source
Distributed Compressive Sensing
, 2009 42 pages, 6 figures.
Michael B. Wakin +4 more
openaire +2 more sources
Understanding and measuring mechanical signals in the tumor stroma
FEBS Open Bio, EarlyView.This review discusses cancer‐associated fibroblast subtypes and their functions, particularly in relation to extracellular matrix production, as well as the development of 3D models to study tumor stroma mechanics in vitro. Several quantitative techniques to measure tissue mechanical properties are also described, to emphasize the diagnostic and ...
Fàtima de la Jara Ortiz +3 more
wiley +1 more source
FEBS Open Bio, EarlyView.The tumor microenvironment is a dynamic, multifaceted complex system of interdependent cellular, biochemical, and biophysical components. Three‐dimensional in vitro models of the tumor microenvironment enable a better understanding of these interactions and their impact on cancer progression and therapeutic resistance.
Salma T. Rafik +3 more
wiley +1 more source
Hamming Compressed Sensing [PDF]
, 2011 Compressed sensing (CS) and 1-bit CS cannot directly recover quantized signals and require time consuming recovery. In this paper, we introduce \textit{Hamming compressed sensing} (HCS) that directly recovers a k-bit quantized signal of dimensional $n ...
Tao, Dacheng, Zhou, Tianyi
core
, 2008 Compressed Sensing aims to capture attributes of $k$-sparse signals using very few measurements. In the standard Compressed Sensing paradigm, the $\m\times \n$ measurement matrix $\A$ is required to act as a near isometry on the set of all $k$-sparse ...
Calderbank, Robert +2 more
core +3 more sources