Classical minimum entropy set cover problem relies on the finding the most likely assignment between the set of observations and the given set of their types. The solution is described by such partition of data space which minimizes the entropy of the distribution of types. The problem finds a natural application in the machine learning, clustering and data classification. In this paper we show...

This report proposes a new coding method, which realizes lossless, near-lossless and lossy coding with a unified single algorithm. The method is based on a lifting-structured lossless DCT, which maps an "integer" input vector to also an "integer" output vector. The proposed method can be used as not only a high performance "lossless" encoder but also a "lossy" encoder compatible to conventional...

At present, the most successful methods for lossy source compression are sample-function adaptive coders. Prominent examples of these techniques are the still image compression methods utilizing wavelet expansions and tree structures, such as the zero-tree method or the SPIHT algorithm, and variable rate speech coders that allocate bits to parameters within a frame based upon the classification...

Although wireless sensor networks have been widely studied, the special characteristics of these networks provide challenges from many points of view. One such challenge is time synchronization. The design and the performance of time synchronization protocols in wireless sensor networks have been examined analytically and using simulations for different network scenarios. However an empirical a...

In this paper, Intelligent water drop algorithm (IWD) is used to analyze single overhead line connected to grid-grounded arrester. In this approach, at first Norton’s equivalent circuit of the overhead line over lossy soil is computed by method of moments (MoM) and then for the problem under consideration, a nonlinear equivalent circuit in the frequency domain is proposed. Finally applying inte...

This paper presents a new algorithm for the lossy compression of scalar data defined on 2D or 3D regular grids, with topological control. Certain techniques allow users to control the pointwise error induced by the compression. However, in many scenarios it is desirable to control in a similar way the preservation of higher-level notions, such as topological features , in order to provide guara...

The JBIG2 standard for lossy and lossless bi-level image coding is a very flexible encoding strategy based on pattern matching techniques. The encoder collects a set of symbols in a dictionary and encodes a page by reference to the dictionary symbols. JBIG2 allows the encoder to view all symbols and choose a good set for the dictionary. We propose a two-pass technique for choosing the dictionar...

The discrete time tube model is well established in speech analysis and synthesis providing a simplified modeling of the vocal tract. The standard lossless tube model is extended by introducing frequency dependent losses. In this contribution it is shown how the lossy vocal tract model can be used for speech production. For that purpose the vocal tract areas of this model can be estimated from ...

In this paper, lossy compression of 3D MR images of the human brain is associated with a segmentation algorithm, in the context of an interactive brain sulci delineation application. Innuence of compression losses is analyzed according to the segmentation results. Lossy compression is performed by subband coding leading to a multiresolution representation of the image. Wavelets are adapted for ...

In this work, we present a new content-based watermarking approach that uses geometric warping to embed watermarks with high robustness to strong lossy compression. The issue of hard decisions related to content-based watermarking is discussed and it is explained why hard decisions can involve bit errors in the watermark extraction process. This work contains a solution to prevent hard decision...