Results 31 to 40 of about 18,243 (295)
Broadband Microwave Spectrum Sensing Based on Photonic RF Channelization and Compressive Sampling
IEEE Photonics Journal, 2020 A novel approach to realize broadband microwave spectrum sensing based on photonic RF channelization and compressive sampling (CS) is proposed. The photonic RF channelization system is used to slice the input broadband signal into multiple sub-channel ...
Bo Yang +5 more
doaj +1 more source
New Directions In Sparse Sampling and Estimation For Underdetermined Systems [PDF]
, 2013 A central objective in signal processing is to infer meaningful information from a set of measurements or data. While most signal models have an overdetermined structure (the number of unknowns less than the number of equations), traditionally very few ...
Piya Pal, Pal, Piya
core +1 more source
A Novel Strategy for Radar Imaging Based on Compressive Sensing [PDF]
, 2010 Radar data have already proven to be compressible with no significant losses for most of the applications in which it is used. In the framework of information theory, the compressibility of a signal implies that it can be decomposed onto a reduced set of
López-Dekker, Paco +8 more
core +1 more source
Dynamic range analysis of one-bit compressive sampling with time-varying thresholds
The Journal of Engineering, 2019 From the point of view of statistical signal processing, the dynamic range for one-bit quantisers with time-varying thresholds is studied. Maximum tolerable amplitudes, minimum detectable amplitudes and dynamic ranges of this one-bit sampling approach ...
Xiaofeng Zhu, Liang Huang, Ziqian Wang
doaj +1 more source
Sparsity and incoherence in compressive sampling [PDF]
Inverse Problems, 2007 We consider the problem of reconstructing a sparse signal $x^0\in\R^n$ from a limited number of linear measurements. Given $m$ randomly selected samples of $U x^0$, where $U$ is an orthonormal matrix, we show that $\ell_1$ minimization recovers $x^0$ exactly when the number of measurements exceeds \[ m\geq \mathrm{Const}\cdotμ^2(U)\cdot S\cdot\log n, \]
Candès, Emmanuel, Romberg, Justin
openaire +3 more sources
On Compressing Collections of Substring Samples. [PDF]
, 2022 Peer ...
Golnaz Badkobeh +3 more
openaire +1 more source
Sample Distortion for Compressed Imaging [PDF]
IEEE Transactions on Signal Processing, 2013 We propose the notion of a sample distortion (SD) function for independent and identically distributed (i.i.d) compressive distributions to fundamentally quantify the achievable reconstruction performance of compressed sensing for certain encoder-decoder pairs at a given sampling ratio.
Chunli Guo, Mike E. Davies 0001
openaire +2 more sources
Non-Cooperative Low-Complexity Detection Approach for FHSS-GFSK Drone Control Signals
IEEE Open Journal of the Communications Society, 2020 The commercial drone market has substantially grown over the past few years. While providing numerous advantages in various fields and applications, drones also provide ample opportunities for misuse by irresponsible hobbyists or malevolent actors.
Dan Mototolea +3 more
doaj +1 more source
Audio Watermarking Combined with Compressive Sampling Based on QIM and DST-QR Techniques
Jurnal Elektronika dan Telekomunikasi, 2019 Abuse is not only done to copy or distribute data but also to the digital copyright labels. There is a way to protect data by inserting or hiding a piece of certain information, namely a watermarking technique.
Irma Safitri +2 more
doaj +1 more source
PhotoniX, 2022 High-throughput imaging is highly desirable in intelligent analysis of computer vision tasks. In conventional design, throughput is limited by the separation between physical image capture and digital post processing.
Zhihong Zhang +7 more
doaj +1 more source