Wyner-Ziv (WZ) video coding – a particular case of distributed video coding (DVC) – is a new video coding paradigm based on two major Information Theory results: the Slepian-Wolf and Wyner-Ziv theorems. Most of the solutions available in the literature, model the correlation noise between the original frame and the so-called side information by virtual channel. However most of the DVC solutions...

In this paper, we extend the results for optimal transmission of the Gaussian channel state via the state-dependent channels to the communications of the Laplacian data. We derive a minimum mean square estimate (MMSE) of the stationary independent identically (i.i.d.) distributed Laplacian channel state corrupted by an additive white Gaussian noise (AWGN) and demonstrate that estimation accurac...

In the context of wavelet denoising and compression, we study minimum description length (MDL) criteria for model selection criteria as exible forms of thresholding. Mixture MDL methods based on a single Laplacian, a two-piece Laplacian, and a generalized Gaussian prior are shown to be adaptive thresholding rules. While achieving mean squared error performance comparable with other popular thre...

In the context of wavelet denoising and compression, we study minimum description length (MDL) criteria for model selection criteria as exible forms of thresholding. Mixture MDL methods based on a single Laplacian, a two-piece Laplacian, and a generalized Gaussian prior are shown to be adaptive thresholding rules. While achieving mean squared error performance comparable with other popular thre...

In the context of wavelet denoising and compression, we study minimum description length (MDL) criteria for model selection criteria as exible forms of thresholding. Mixture MDL methods based on a single Laplacian, a two-piece Laplacian, and a generalized Gaussian prior are shown to be adaptive thresholding rules. While achieving mean squared error performance comparable with other popular thre...

In this paper a new completely unsupervised mesh segmentation algorithm is proposed, which is based on the PCA interpretation of the Laplacian eigenvectors of the mesh and on parametric clustering using Gaussian mixtures. We analyse the geometric properties of these vectors and we devise a practical method that combines single-vector analysis with multiple-vector analysis. We attempt to charact...

In a latent variable model, an overcomplete representation is one in which the number of latent variables is at least as large as the dimension of the data observations. Overcomplete representations have been advocated due to robustness in the presence of noise, the ability to be sparse, and an inherent flexibility in modeling the structure of data [9]. In this report, we modify factor analysis...

in the present study, computational fluid dynamics (cfd) techniques and artificial neural networks (ann) are used to predict the pressure drop value (δp ) of al2o3-water nanofluid in flat tubes. δp  is predicted taking into account five input variables: tube flattening (h), inlet volumetric flow rate (qi  ), wall heat flux (qnw  ), nanoparticle volume fraction (φ) and nanoparticle diameter (dp ...

Capturing dependencies in images in an unsupervised manner is important for many image processing applications. We propose a new method for capturing nonlinear dependencies in images of natural scenes. This method is an extension of the linear Independent Component Analysis (ICA) method by building a hierarchical model based on ICA and mixture of Laplacian distribution. The model parameters are...

This paper studies the problem of fault detection and isolation (FDI) for multi-agent systems (MAS) via complex Laplacian subject to actuator faults. A planar formation of point agents in the plane using simple and linear interaction rules related to complex Laplacian is achieved. The communication network is a directed, and yet connected graph with a fixed topology. The loss of symmetry in the...