Results 41 to 50 of about 243,195 (329)
Computational Complexity versus Statistical Performance on Sparse Recovery Problems [PDF]
We show that several classical quantities controlling compressed sensing performance directly match classical parameters controlling algorithmic complexity.
Boumal, Nicolas+2 more
core +3 more sources
Blind Compressed Sensing [PDF]
The fundamental principle underlying compressed sensing is that a signal, which is sparse under some basis representation, can be recovered from a small number of linear measurements. However, prior knowledge of the sparsity basis is essential for the recovery process.
Yonina C. Eldar, Sivan Gleichman
openaire +2 more sources
Compressive Image Classification using Deterministic Sensing Matrices [PDF]
We look at the use of deterministic sensing matrices for compressed sensing and provide worst-case bounds on the classification accuracy of SVMs on compressively sensed data.
arxiv
Infrared images of power equipment play an important role in power equipment status monitoring and fault identification. Aiming to resolve the problems of low resolution and insufficient clarity in the application of infrared images, we propose a blind ...
Yan Wang+3 more
doaj +1 more source
Experimentally exploring compressed sensing quantum tomography [PDF]
In the light of the progress in quantum technologies, the task of verifying the correct functioning of processes and obtaining accurate tomographic information about quantum states becomes increasingly important.
Bell, B. A.+8 more
core +4 more sources
Compressed Measurements Based Spectrum Sensing for Wideband Cognitive Radio Systems
Spectrum sensing is the most important component in the cognitive radio (CR) technology. Spectrum sensing has considerable technical challenges, especially in wideband systems where higher sampling rates are required which increases the complexity and ...
Taha A. Khalaf+2 more
doaj +1 more source
Compressed Sensing Image Mapping Spectrometer
This paper presents a novel snapshot imaging spectrometer based on the image mapping and compressed sensing concept named Compressed Sensing Image Mapping Spectrometer (CSIMS).
Xiaoming Ding
doaj +1 more source
(Compressed) sensing and sensibility [PDF]
For decades, researchers have built computer models of molecular interactions to predict properties of new molecules (1). These models take the form of potential functions, equations that can be used predict the molecular energy of interaction. Potential functions have very broad applications. Other than ab initio quantum mechanics-based approaches (2),
openaire +2 more sources
Compressive Sensing with Optical Chaos [PDF]
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 +6 more sources
In the past decades, compressed sensing emerges as a promising technique for signal acquisition in low-cost sensor networks. For prolonging the monitoring duration of biosignals, compressed sensing is also exploited for simultaneous sampling and ...
Junxin Chen+3 more
doaj +1 more source