Generalized locally most powerful tests for distributed sparse signal detection
In this paper we tackle distributed detection of a localized phenomenon of interest (POI)
whose signature is sparse via a wireless sensor network. We assume that both the position …
whose signature is sparse via a wireless sensor network. We assume that both the position …
Eigen analysis of flipped Toeplitz covariance matrix for very low SNR sinusoidal signals detection and estimation
O Sharifi-Tehrani, MF Sabahi - Digital Signal Processing, 2022 - Elsevier
Detection and estimation of feeble signals in noise is of great importance in practice. In this
paper, we use the properties of eigen-space and eigen-spectrum of symmetric and Toeplitz …
paper, we use the properties of eigen-space and eigen-spectrum of symmetric and Toeplitz …
Distributed detection of sparse stochastic signals with 1-bit data in tree-structured sensor networks
In this paper, we consider the problem of detection of sparse stochastic signals based on 1-
bit data with tree-structured sensor networks (TSNs). In the literature, distributed detection of …
bit data with tree-structured sensor networks (TSNs). In the literature, distributed detection of …
Detection of sparse stochastic signals with quantized measurements in sensor networks
In this paper, we consider the problem of detection of sparse stochastic signals with
quantized measurements in sensor networks. The observed sparse signals are assumed to …
quantized measurements in sensor networks. The observed sparse signals are assumed to …
Detection of sparse signals in sensor networks via locally most powerful tests
We consider the problem of detection of sparse stochastic signals with a distributed sensor
network. Multiple sensors in the network are assumed to observe sparse signals, which …
network. Multiple sensors in the network are assumed to observe sparse signals, which …
Distributed detection of sparse stochastic signals via fusion of 1-bit local likelihood ratios
In this letter, we consider the detection of sparse stochastic signals with sensor networks
(SNs), where the fusion center (FC) collects 1-bit data from the local sensors and then …
(SNs), where the fusion center (FC) collects 1-bit data from the local sensors and then …
Property investigation on the additive white Gaussian noise after sub-Nyquist sampling
T Gong, Z Liu, C Xie, Z Yang - IEEE Access, 2019 - ieeexplore.ieee.org
The sub-Nyquist sampling (SNS) has emerged as an appealing technique for wideband
signal sampling and has found its applications in many areas, such as, cognitive radios …
signal sampling and has found its applications in many areas, such as, cognitive radios …
Markovian Block Sparse Signal Detection Using One Bit Measurements
This paper presents a novel sparse signal detection scheme designed for a correlated
Markovian Bernoulli-Gaussian sparse signal model, which can equivalently be viewed as a …
Markovian Bernoulli-Gaussian sparse signal model, which can equivalently be viewed as a …