940 research outputs found
Correlations between charge and energy current in ac-driven coherent conductors
We study transport in coherent conductors driven by a time-periodic bias
voltage. We present results of the charge and energy noise and complement them
by a study of the mixed noise, namely the zero-frequency correlator between
charge and energy current. The mixed noise presents interference contributions
and transport contributions, showing features different from those of charge
and energy noise. The mixed noise can be accessed by measuring the correlator
between the fluctuations of the power provided to the system and the charge
current.Comment: 8 pages, 1 figur
Heat-charge mixed noise and thermoelectric efficiency fluctuations
The close relationship between the noise and the thermoelectric conversion is
studied in a quantum dot using a quantum approach based on the non-equilibrium
Green function technique. We show that both the figure of merit and the
efficiency can be written in term of noise and we highlight the central role
played by the correlator between the charge current and the heat current that
we call the mixed noise. After giving the expression of this quantity as an
integral over energy, we calculate it, first in the linear response regime,
next in the limit of small transmission through the barriers (Schottky regime)
and finally in the intermediate regime. We discuss the notion of efficiency
fluctuations and we also see here that the mixed noise comes into play.Comment: Proceeding of the UPON 2015 conferenc
An Efficient Threshold Based Mixed Noise Removal Technique
Removing or reducing noises from image is very important task in image processing. This paper presents an efficient noise removal technique to restore original digital images corrupted by mixed noise. The proposed filtering technique consists of three steps: noisy pixel detection using fuzzy flag, mixed noise filtering step and calculating threshold value remove the pixel value with replacement conditions. Noises in this methodology are the combination of gaussian noise and salt and pepper noise. This methodology reduces the mixed noise without lossing edges sharpness and information. This methodology gives better results existing many fuzzy algorithms. The proposed technique shows better peak signal noise ratio result with thresholding replacement conditions. Hence, this mixed noise removal technique finds application in numerous segments of image process like digital tv, medical image process, camera, police work systems etc. Wiener filter is used for image enhancement
Hyperspectral Image Restoration via Total Variation Regularized Low-rank Tensor Decomposition
Hyperspectral images (HSIs) are often corrupted by a mixture of several types
of noise during the acquisition process, e.g., Gaussian noise, impulse noise,
dead lines, stripes, and many others. Such complex noise could degrade the
quality of the acquired HSIs, limiting the precision of the subsequent
processing. In this paper, we present a novel tensor-based HSI restoration
approach by fully identifying the intrinsic structures of the clean HSI part
and the mixed noise part respectively. Specifically, for the clean HSI part, we
use tensor Tucker decomposition to describe the global correlation among all
bands, and an anisotropic spatial-spectral total variation (SSTV)
regularization to characterize the piecewise smooth structure in both spatial
and spectral domains. For the mixed noise part, we adopt the norm
regularization to detect the sparse noise, including stripes, impulse noise,
and dead pixels. Despite that TV regulariztion has the ability of removing
Gaussian noise, the Frobenius norm term is further used to model heavy Gaussian
noise for some real-world scenarios. Then, we develop an efficient algorithm
for solving the resulting optimization problem by using the augmented Lagrange
multiplier (ALM) method. Finally, extensive experiments on simulated and
real-world noise HSIs are carried out to demonstrate the superiority of the
proposed method over the existing state-of-the-art ones.Comment: 15 pages, 20 figure
Mixed Noise Removal by Processing of Patches
Sonar images are degraded by mixed noise which has an adverse impact on detection and classification of underwater objects. Existing denoising methods of sonar images remove either additive noise or multiplicative noise. In this study, the mixed noise in sonar images, the additive Gaussian noise and the multiplicative speckle effect are handled by the data adaptive methods. A patch based denoising is applied in two phases to remove the additive Gaussian and multiplicative speckle noises. In the first phase, the adaptive processing of local patches is used to remove the additive Gaussian noise by exploiting the sonar image local sparsity. The PCA and SVD methods are used for denoising the noisy image patches and blocks of patches. In the second phase, the weighted maximum likelihood denoising of the nonlocal patches reduces the speckle effect by exploiting the non-local similarity in a probability distribution. Experiments on side scan sonar images are conducted and the results show the importance of removing both the additive and multiplicative components from the sonar images
Channel Capacity and Bounds In Mixed Gaussian-Impulsive Noise
Communication systems suffer from the mixed noise consisting of both
non-Gaussian impulsive noise (IN) and white Gaussian noise (WGN) in many
practical applications. However, there is little literature about the channel
capacity under mixed noise. In this paper, we prove the existence of the
capacity under p-th moment constraint and show that there are only finite mass
points in the capacity-achieving distribution. Moreover, we provide lower and
upper capacity bounds with closed forms. It is shown that the lower bounds can
degenerate to the well-known Shannon formula under special scenarios. In
addition, the capacity for specific modulations and the corresponding lower
bounds are discussed. Numerical results reveal that the capacity decreases when
the impulsiveness of the mixed noise becomes dominant and the obtained capacity
bounds are shown to be very tight
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