Towards Parallel Decoding with Compressive Sensing in Multi-Reader Large-Scale RFID System

2021 ◽  
Author(s):  
Wei Sun
Keyword(s):  
Compressive Sensing ◽  
Large Scale ◽  
Rfid System ◽  
Parallel Decoding

scholarly journals Large-scale sparse reconstruction through partitioned compressive sensing

2014 ◽  
Author(s):  
Si Qin ◽  
Yimin D. Zhang ◽  
Qisong Wu ◽  
Moeness G. Amin
Keyword(s):  
Compressive Sensing ◽  
Large Scale ◽  
Sparse Reconstruction

Towards efficient large-scale RFID system management

2015 ◽  
Author(s):  
Haoxiang Liu
Keyword(s):  
Large Scale ◽  
System Management ◽  
Rfid System

Large scale active RFID system utilizing ZigBee networks

2011 ◽  
Author(s):  
Hyuntae Cho ◽  
Hyunsung Jang ◽  
Yunju Baek
Keyword(s):  
Large Scale ◽  
Active Rfid ◽  
Rfid System ◽  
Zigbee Networks

scholarly journals Extended Dai-Yuan conjugate gradient strategy for large-scale unconstrained optimization with applications to compressive sensing

Filomat ◽  
2018 ◽  
Vol 32 (6) ◽  
pp. 2173-2191
Author(s):  
Hamid Esmaeili ◽  
Majid Rostami ◽  
Morteza Kimiaei
Keyword(s):  
Compressive Sensing ◽  
Unconstrained Optimization ◽  
Conjugate Gradient ◽  
Large Scale ◽  
Optimization Problems ◽  
Convex Combination ◽  
Step Size ◽  
Convergence Results ◽  
Spectral Conjugate Gradient ◽  
Large Scale Unconstrained Optimization

We present a new spectral conjugate gradient method based on the Dai-Yuan strategy to solve large-scale unconstrained optimization problems with applications to compressive sensing. In our method, the numerator of conjugate gradient parameter is a convex combination from the maximum gradient norm value in some preceding iterates and the current gradient norm value. This combination will try to produce the larger step-size far away from the optimizer and the smaller step-size close to it. In addition, the spectral parameter guarantees the descent property of the new generated direction in each iterate. The global convergence results are established under some standard assumptions. Numerical results are reported which indicate the promising behavior of the new procedure to solve large-scale unconstrained optimization and compressive sensing problems.

Load Balance Using Compressive Sensing Theory in Large-Scale Wireless Sensor Network

2011 ◽  
Vol 9 (5) ◽  
pp. 1855-1859 ◽  
Author(s):  
Ying Zhang ◽  
Guiling Sun ◽  
Weixiang Li
Keyword(s):  
Wireless Sensor Network ◽  
Compressive Sensing ◽  
Sensor Network ◽  
Load Balance ◽  
Large Scale ◽  
Wireless Sensor

Tree Structure Sparsity Pattern Guided Convex Optimization for Compressive Sensing of Large-Scale Images

2017 ◽  
Vol 26 (2) ◽  
pp. 847-859 ◽  
Author(s):  
Wei-Jie Liang ◽  
Gang-Xuan Lin ◽  
Chun-Shien Lu
Keyword(s):  
Convex Optimization ◽  
Compressive Sensing ◽  
Large Scale ◽  
Tree Structure ◽  
Sparsity Pattern

scholarly journals Medical Image Encryption and Compression Scheme Using Compressive Sensing and Pixel Swapping Based Permutation Approach

2015 ◽  
Vol 2015 ◽  
pp. 1-9 ◽  
Author(s):  
Li-bo Zhang ◽  
Zhi-liang Zhu ◽  
Ben-qiang Yang ◽  
Wen-yuan Liu ◽  
Hong-feng Zhu ◽  
...  
Keyword(s):  
Compressive Sensing ◽  
Medical Image ◽  
Large Scale ◽  
Image Transmission ◽  
Security Level ◽  
Compression Scheme ◽  
Diffusion Type ◽  
Public Networks ◽  
Chebyshev Map ◽  
Plain Image

This paper presents a solution to satisfy the increasing requirements for secure medical image transmission and storage over public networks. The proposed scheme can simultaneously encrypt and compress the medical image using compressive sensing (CS) and pixel swapping based permutation approach. In the CS phase, the plain image is compressed and encrypted by chaos-based Bernoulli measurement matrix, which is generated under the control of the introduced Chebyshev map. The quantized measurements are then encrypted by permutation-diffusion type chaotic cipher for the second level protection. Simulations and extensive security analyses have been performed. The results demonstrate that at a large scale of compression ratio the proposed cryptosystem can provide satisfactory security level and reconstruction quality.

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