Application of compressive sensing techniques in distributed sensor networks: A survey
T Wimalajeewa, PK Varshney - ar**%20Spread%20Spectrum%20Signals.pdf" data-clk="hl=fr&sa=T&oi=gga&ct=gga&cd=1&d=3536801108326293894&ei=Tb2tZ9eUEYqy6rQPl5KnWA" data-clk-atid="hiH_ht49FTEJ" target="_blank">[PDF] edi-info.ir
Compressive sampling for detection of frequency-hop** spread spectrum signals
In this paper, methods for detection of frequency-hop** spread spectrum (FHSS) signals
from compressive measurements are proposed. Rapid switching of the carrier frequency in a …
from compressive measurements are proposed. Rapid switching of the carrier frequency in a …
Sparse signal detection with compressive measurements via partial support set estimation
In this paper, we consider the problem of sparse signal detection based on partial support
set estimation with compressive measurements in a distributed network. Multiple nodes in …
set estimation with compressive measurements in a distributed network. Multiple nodes in …
Novelty detection in images by sparse representations
We address the problem of automatically detecting anomalies in images, ie, patterns that do
not conform to those appearing in a reference training set. This is a very important feature for …
not conform to those appearing in a reference training set. This is a very important feature for …
Compressive detection of random subspace signals
The problem of compressive detection of random subspace signals is studied. We consider
signals modeled as s= Hx where H is an N× K matrix with K≤ N and x~ N (0 K, 1, σ∞ 2 IK) …
signals modeled as s= Hx where H is an N× K matrix with K≤ N and x~ N (0 K, 1, σ∞ 2 IK) …
[PDF][PDF] Compressive sensing based signal processing in wireless sensor networks: A survey
T Wimalajeewa, PK Varshney - ar** new signal
processing methods to manage the deluge of data caused by advances in sensing, imaging …
processing methods to manage the deluge of data caused by advances in sensing, imaging …
Algorithms for change detection with sparse signals
We consider the change detection problem where the pre-change observation vectors are
purely noise and the post-change observation vectors are noise-corrupted compressive …
purely noise and the post-change observation vectors are noise-corrupted compressive …
Detection tests using sparse models, with application to hyperspectral data
The problem of finding efficient methods for the detection of unknown sparse signals buried
in noise is addressed. We present two detection tests adapted to sparse signals, based on …
in noise is addressed. We present two detection tests adapted to sparse signals, based on …
Detection of sparse random signals using compressive measurements
BSMR Rao, S Chatterjee… - 2012 IEEE International …, 2012 - ieeexplore.ieee.org
We consider the problem of detecting a sparse random signal from the compressive
measurements without reconstructing the signal. Using a subspace model for the sparse …
measurements without reconstructing the signal. Using a subspace model for the sparse …