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Compressive Sensing over OFDM Systems

open access: yesJournal of Kufa for Mathematics and Computer, 2021
Communications development is the fastest-growing Nowadays, so the need and the constant demand for faster and more reliable communication methods have increased. Here, the compressive sensing appeared to meet this need.
Zainab Al-Shably, Zahir Hussain
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

Analysis of the Measurement Matrix in Directional Predictive Coding for Compressive Sensing of Medical Images

open access: yesELCVIA Electronic Letters on Computer Vision and Image Analysis, 2022
Compressive sensing of 2D signals involves three fundamental steps: sparse representation, linear measurement matrix, and recovery of the signal. This paper focuses on analyzing the efficiency of various measurement matrices for compressive sensing of ...
Hepzibah Christinal A   +4 more
doaj   +1 more source

SPECTRUM SENSING OF WIDE BAND SIGNALS BASED ON ENERGY DETECTION WITH COMPRESSIVE SENSING

open access: yesJournal of Engineering and Sustainable Development, 2020
Compressive sensing (CS) technique is used to solve the problem of high sampling rate with wide band signal spectrum sensing where high speed analogue to digital converter is needed to do that. This leads to difficult hardware implementation, large time
Ali Mohammad A. AL-Hussain   +1 more
doaj   +3 more sources

Deterministic Sensing Matrices in Compressive Sensing: A Survey

open access: yesThe Scientific World Journal, 2013
Compressive sensing is a sampling method which provides a new approach to efficient signal compression and recovery by exploiting the fact that a sparse signal can be suitably reconstructed from very few measurements.
Thu L. N. Nguyen, Yoan Shin
doaj   +1 more source

Image Watermarking pada Citra Medis menggunakan Compressive Sensing berbasis Stationary Wavelet Transform

open access: yesJurnal Elkomika, 2020
ABSTRAK Watermarking pada citra medis dilakukan untuk melindungi hak kepemilikan dan keaslian sebuah citra medis. Proses embedding dan extraction dirancang menggunakan metode Stationary Wavelet Transform (SWT) dan Statistical Mean Manipulation (SMM ...
YASQI HAFIZHANA   +3 more
doaj   +1 more source

A software companion for compressively sensed time–frequency processing of sparse nonstationary signals

open access: yesSoftwareX, 2018
Compressive sensing is a computational framework for acquisition and processing of sparse signals at sampling rates below the rates mandated by the Nyquist sampling theorem.
Ervin Sejdić   +2 more
doaj   +1 more source

Efficient Lossy Compression for Compressive Sensing Acquisition of Images in Compressive Sensing Imaging Systems

open access: yesSensors, 2014
Compressive Sensing Imaging (CSI) is a new framework for image acquisition, which enables the simultaneous acquisition and compression of a scene. Since the characteristics of Compressive Sensing (CS) acquisition are very different from traditional image
Xiangwei Li   +4 more
doaj   +1 more source

A New Method for EEG Compressive Sensing

open access: yesAdvances in Electrical and Computer Engineering, 2012
The paper investigates the possibility of using compressive sensing techniques for the acquisition and reconstruction of EEG signals containing the evoked potential P300. A method of EEG compressive sensing based on the physiological correlation of EEG
FIRA, M., GORAS, L.
doaj   +1 more source

Adaptive compressive sensing of images using error between blocks

open access: yesInternational Journal of Distributed Sensor Networks, 2018
Block compressive sensing of image results in blocking artifacts and blurs when reconstructing images. To solve this problem, we propose an adaptive block compressive sensing framework using error between blocks.
Ran Li, Xiaomeng Duan, Yongfeng Lv
doaj   +1 more source

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