compressive sampling
Audio Watermarking Combined with Compressive Sampling Based on QIM and DST-QR Techniques
... In [8] and [9] as our previous research, there was also a method named multicarrier modulation to recover data from incomplete information. In [8], the proposed method has much lower imperceptibility level than the ...
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Compressive Sampling Multispectral Imaging and Unmixing Method for Fluorescent Imaging
... DMD. Compressive sampling (CS) is an efficient signal acquisition protocol that is able to reconstruct the signal from an apparent incomplete set of measurements by utilizing the fact that many natural ...
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EARLY DETECTION OF ROGUE WAVES USING COMPRESSIVE SAMPLING
... the compressive sampling for the early detection of the rogue ...the compressive sampling technique can become an efficient tool for the rogue wave early warn- ing and measurement ...the ...
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Compressive Sampling of EEG Signals with Finite Rate of Innovation
... Shannon’s sampling theory cannot be applied to sampling EEG ...new sampling theory known as compressive sampling or compressed sensing ...directly. Compressive sampling, ...
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Towards Compressive Sampling and Fine-Grained Indoor Fingerprint Positioning
... based compressive sampling and fine- grained clustering matching method to solve above trade- off ...the sampling work, we use less sample data to estimate others by constructing Gaussian processes ...
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Efficient compressive sampling of spatially sparse fields in wireless sensor networks
... Wireless sensor networks (WSNs), i.e., networks of autonomous, wireless sensing nodes spatially deployed over a geographical area, are often faced with acquisition of spatially sparse fields. In this paper, we present a ...
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One bit compressive sampling via ℓ 0 minimization
... 1-bit compressive sampling algorithms, the binary iterative hard thresholding (BIHT) [4] exhibits its superior performance in both reconstruction error and as well as consistency via numerical simulations ...
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Compressive sampling based CFO estimation with exploited features
... In CS theory, the measurement matrix plays an impor- tant role to determine the performance of reconstruction [6, 7], because a more efficient measurement matrix for the compressive sampling leads to the ...
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MRCS: matrix recovery based communication efficient compressive sampling on temporal spatial data of dynamic scale sparsity in large scale environmental IoT networks
... in compressive sensing and reduce the recovery quality severely, the recovery quality of the proposed method still keeps the fidelity of event readings, which is about 10 times (10 db) better than typical ...
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Methods to reduce perturbation effects in compressive sampling
... With compressive sampling (CS), few measurements or samples will be enough for signal reconstruction as long as the signal can be represented in a basis do- main and the coefficients are ...
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A fast and accurate algorithm for ℓ 1 minimization problems in compressive sampling
... This section is devoted to showing the numerical perfor- mance of the proposed algorithms for compressive sam- pling. We use NESTA [18] and dual alternating direction method (DADM) [23] as a comparison. In the ...
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Deterministic compressive sampling for high-quality image reconstruction of ultrasound tomography
... compressed sampling system that ensures the ability to successfully reconstruct sparse sig- ...compressed sampling technique inherits some advantages over random one, such as more effective recovery time, ...
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Compressive sampling of swallowing accelerometry signals using time-frequency dictionaries based on modulated discrete prolate spheroidal sequences
... Given the CS framework, the immediate question is how to define the sensing matrix F , that is the bases used in the recovery of the signal. Most commonly used sensing matrices are random matrices with independent ...
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Compressive Split-Step Fourier Method
... 2.3. Review of the Compressive Sampling. Since its first appearance in literature, compressive sampling (CS) has drawn the attention of many researchers. Today it is widely used in various ...
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Impulse Radio UWB Signal Detection Based on Compressed Sensing
... high sampling rate is a challenge for ultra-wideband (UWB) ...on compressive sampling matching pursuit ...the sampling rate required by the detection and provides a better performance in case ...
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Image Fusion Based On Sparse Sampling Method And Hybrid Discrete Cosine Transformation
... Compressive Sensing (CS) Compressive sensing is one of the most predominant tools for acquiring and reconstructing an input signal ...sparse sampling or compressive ...
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An Agile and Robust Sparse Recovery Method for MR Images Based on Selective k-space Acquisition and Artifacts Suppression
... Abstract—Magnetic Resonance Imaging (MRI) has some attractive advantages over other medical imaging techniques. Its widespread application as a medical diagnostic tool is however hindered by its long acquisition time as ...
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Compressive closeness in networks
... is compressive sensing (aka compressive sampling) which performs a few indirect end-to-end measurements on a signal x and recovers a good sparse approxi- mation of that ...of compressive ...
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Compressive video sampling
... Compressive sampling is a novel framework that exploits sparsity of a signal in a transform domain to perform sam- pling below the Nyquist ...pressive sampling to significantly reduce the ...
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Compressive Sensing based Leakage Sampling and Reconstruction: A First Study
... existing compressive sampling techniques that are used to eliminate information re- dundancy on power ...the sampling rate of the oscilloscope is much higher than the bandwidth of the leaky ...high ...
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