Results 31 to 40 of about 5,109 (308)

Compressive Sensing for High-Resolution Direction-of-Arrival Estimation via Iterative Optimization on Sensing Matrix

open access: yesInternational Journal of Antennas and Propagation, 2015
A novel compressive sensing- (CS-) based direction-of-arrival (DOA) estimation algorithm is proposed to solve the performance degradation of the CS-based DOA estimation in the presence of sensing matrix mismatching. Firstly, a DOA sparse sensing model is
Hongtao Li, Chaoyu Wang, Xiaohua Zhu
doaj   +1 more source

Automated Firmware Generation for Compressive Sensing on Heterogeneous Hardware

open access: yesSensors, 2022
In this paper, a model-based firmware generator is presented towards complex sampling schemes. The framework is capable of automatically generating a fixed-rate Shannon-compliant acquisition scheme, as well as a variable-rate compressive sensing ...
Rens Baeyens   +4 more
doaj   +1 more source

Applicazione dell'algoritmo di nesterov alla tecnica di compressive sensing in reti di sensori radio [PDF]

open access: yes, 2022
In questa tesi si analizza una tecnica di compressione e ricostruzione di segnali, il Compressive Sensing (CS), e la sua applicazione in un protocollo innovativo per la raccolta e la ricostruzione dei dati di una rete di sensori radio.
Zordan, Davide
core  

A hybrid watermarking scheme with CS theory for security of multimedia data

open access: yesJournal of King Saud University: Computer and Information Sciences, 2019
A hybrid watermarking scheme for multimedia data such as digital image, digital video is proposed in this paper. The scheme utilizes various image processing transforms and Compressive Sensing (CS) to achieved fragility and security for multimedia data ...
Rohit Thanki   +2 more
doaj   +1 more source

Compressive Sensing Based on Mesoscopic Chaos of Silicon Optomechanical Photonic Crystal

open access: yesIEEE Photonics Journal, 2020
Compressive sensing (CS) is an effective technique that can compress and recover sparse signals below the Nyquist-Shannon sampling theorem restriction.
Pengfei Guo   +6 more
doaj   +1 more source

Application of Compressive Sensing in the Presence of Noise for Transient Photometric Events

open access: yesSignals, 2022
Compressive sensing is a simultaneous data acquisition and compression technique, which can significantly reduce data bandwidth, data storage volume, and power. We apply this technique for transient photometric events. In this work, we analyze the effect
Asmita Korde-Patel   +2 more
doaj   +1 more source

An MCM-Enhanced Compressive Sensing for Weak Fault Feature Extraction of Rolling Element Bearings under Variable Speeds

open access: yesShock and Vibration, 2020
The compressive sensing (CS) theory provides a new slight to the big-data problem led by the Shannon sampling theorem in rolling element bearings condition monitoring, where the measurement matrix of CS tends to be designed by the random matrix (RM) to ...
Ya He, Kun Feng, Minghui Hu, Jinmiao Cui
doaj   +1 more source

A Novel Image Compressive Sensing Method Based on Complex Measurements

open access: yes, 2011
Compressive sensing (CS) has emerged as an efficient signal compression and recovery technique, that exploits the sparsity of a signal in a transform domain to perform sampling and stable recovery.
Xiang, Wei   +5 more
core   +1 more source

AN IMPROVEMENT OF RESOURCE CONSUMPTION IN WIRELESS SENSOR NETWORK (WSN) USING COMPRESSIVE SENSING

open access: yesMalaysian Journal of Computing, 2022
Wireless Sensor Network (WSN) refers to a group of spatially dispersed and dedicated sensors designed to monitor and record the physical conditions of the environment and organise the data collected at a central location.
Maizatul Akmal Ibrahim   +1 more
doaj   +1 more source

Automatic Modulation Recognition Using Compressive Cyclic Features

open access: yesAlgorithms, 2017
Higher-order cyclic cumulants (CCs) have been widely adopted for automatic modulation recognition (AMR) in cognitive radio. However, the CC-based AMR suffers greatly from the requirement of high-rate sampling.
Lijin Xie, Qun Wan
doaj   +1 more source

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