Our motivation, which originates from the psychological and physiological evidences of component-based representations in the brain, is to find neural methods that can efficiently search for structures. Here, an architecture made of coupled parallel working reconstruction subnetworks is presented. Each subnetwork utilizes non-negativity constraint on the generative weights and on the internal r...

In this work we address the problem of Language identification (LI) on short segments of text. The central idea is to compute the entropy of a document in different contexts and assign it to the category where the entropy is maximal. Only word distributions are needed for the task, no other training is done. For LI the contexts are the languages, and classification is done by just evaluating th...

Joint space-frequency segmentation is a relatively new image compression technique that finds the rate-distortion optimal representation of an image from a large set of possible spacefrequency partitions and quantizer combinations. As such, the method is especially effective when the images to code are statistically inhomogeneous, which is certainly the case in the ultrasound modality. Unfortun...

This investigation deals with the numerical simulation of entropy generation at mixed convection flow in a lid-driven saturated porous cavity submitted to a magnetic field. The magnetic field is applied in the direction that is normal to the cavity cross section. The governing equations, written in the Darcy–Brinkman–Forchheimer formulation, are solved using a numerical code based on the Contro...

Programmers are often required to develop in multiple languages. In an effort to study the effects of programming language fragmentation on productivity—and ultimately on a programmer’s problem solving abilities—we propose a metric, language entropy, for characterizing the distribution of an individual’s development efforts across multiple programming languages. To evaluate this metric, we pres...

Two methods to overcome the problems with large vector quantization (VQ) codebooks are lattice VQ (LVQ) and product codes. The approach described in this paper takes advantage of both methods by applying residual VQ with LVQ at all stages. Using LVQ in conjunction with entropy coding is strongly motivated by the fact that entropy constrained but structurally unconstrained VQ design leads to mor...

We present new numerical models for computing transitional or rarefied gas flows as described by the Boltzmann-BGK and BGK-ES equations. We first propose a new discrete-velocity model, based on the entropy minimization principle. This model satisfies the conservation laws and the entropy dissipation. Moreover, the problem of conservation and entropy for axisymmetric flows is investigated. We fi...

We propose a new vector quantization approach, which consists of Hidden Markov Models(HMMs) and entropy coding scheme. The entropy coding system is determined depending on the speech status modeled by HMMs, so the proposing approach can adaptively allocate suitable numbers of bits to the codewords. This approach realizes about 0.3[dB] coding gain in cepstrum distance(8 states HMMs). In other wo...

The detection of covert channels has quickly become a vital need due to their pervasive nature and the increasing popularity of the Internet. In recent years, new and innovative methods have been proposed to aid in the detection of covert channels. Existing detection schemes are often too specific and are ineffective against new covert channels. In this paper, we expound upon previous work done...

Eukaryote genomes contain excessively introns, intergenic and other non-genic sequences that appear to have no vital functional role or phenotype manifestation. Their existence, a long-standing puzzle, is viewed from the principle of increasing entropy. According to thermodynamics of open systems, genomes evolve toward diversity by various mechanisms that increase, decrease and distribute genom...