Evolution of non-stationary processes and some maximum entropy principles

Preda, Vasile; Băncescu, Irina

doi:10.2478/awutm-2018-0015

Cited by 3 publications

(1 citation statement)

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“…Awad-Shannon entropy is intensively studied, especially because of its applications in microchannels (see [22][23][24][25][26]). At the same time, Varma entropy, introduced in [27], is now very actual (see [28][29][30][31]).…”

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confidence: 99%

Ordering Awad–Varma Entropy and Applications to Some Stochastic Models

Sfetcu

Preda

2021

Mathematics

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We consider a generalization of Awad–Shannon entropy, namely Awad–Varma entropy, introduce a stochastic order on Awad–Varma residual entropy and study some properties of this order, like closure, reversed closure and preservation in some stochastic models (the proportional hazard rate model, the proportional reversed hazard rate model, the proportional odds model and the record values model).

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Section: Introductionmentioning

confidence: 99%

Ordering Awad–Varma Entropy and Applications to Some Stochastic Models

Sfetcu

Preda

2021

Mathematics

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Varma Quantile Entropy Order

Sfetcu

2021

Analele Universitatii "Ovidius" Constanta - Seria Matematica

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Using Probabilistic Models for Data Compression

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Our research objective is to improve the Huffman coding efficiency by adjusting the data using a Poisson distribution, which avoids the undefined entropies too. The scientific value added by our paper consists in the fact of minimizing the average length of the code words, which is greater in the absence of applying the Poisson distribution. Huffman Coding is an error-free compression method, designed to remove the coding redundancy, by yielding the smallest number of code symbols per source symbol, which in practice can be represented by the intensity of an image or the output of a mapping operation. We shall use the images from the PASCAL Visual Object Classes (VOC) to evaluate our methods. In our work we use 10,102 randomly chosen images, such that half of them are for training, while the other half is for testing. The VOC data sets display significant variability regarding object size, orientation, pose, illumination, position and occlusion. The data sets are composed by 20 object classes, respectively: aeroplane, bicycle, bird, boat, bottle, bus, car, motorbike, train, sofa, table, chair, tv/monitor, potted plant, person, cat, cow, dog, horse and sheep. The descriptors of different objects can be compared to give a measurement of their similarity. Image similarity is an important concept in many applications. This paper is focused on the measure of similarity in the computer science domain, more specifically information retrieval and data mining. Our approach uses 64 descriptors for each image belonging to the training and test set, therefore the number of symbols is 64. The data of our information source are different from a finite memory source (Markov), where its output depends on a finite number of previous outputs. When dealing with large volumes of data, an effective approach to increase the Information Retrieval speed is based on using Neural Networks as an artificial intelligent technique.

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Evolution of non-stationary processes and some maximum entropy principles

Abstract: This paper studies, by using the speed-gradient principle, the evolution of non-stationary processes in the context of maximization of Varma, weighted Rényi, weighted Varma and Rényi-Tsallis of order α entropies.

Cited by 3 publications

References 26 publications

Ordering Awad–Varma Entropy and Applications to Some Stochastic Models

Ordering Awad–Varma Entropy and Applications to Some Stochastic Models

Varma Quantile Entropy Order

Using Probabilistic Models for Data Compression

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