Estimation of information entropy based on its visualization

• Autorzy: Cholewa M. , Palys M.
• Języki publikacji: EN

Abstrakty

EN

This paper describes the method which allows an estimation of information entropy in the meaning of Shannon. The method is suitable to an estimation which sample has a higher value of information entropy. Several algorithms have been used to estimate entropy, assuming that they do it faster. Each algorithm has calculated this value for several text samples. Then analysis has verified which comparisons of the two samples were correct. It has been found that the probabilistic algorithm is the fastest and most effective in returning the estimated value of entropy.

Słowa kluczowe

EN

Shannon's entropy; information theory; visualization

PL

entropia Shannona; teoria informacji; wizualizacja

• Wydawca: University of Silesia, Institute of Informatics, Computer Systems Department
• Czasopismo: Journal of Medical Informatics & Technologies
• Rocznik: 2017
• Tom: Vol. 26
• Strony: 18--25
• Opis fizyczny: Bibliogr. 13 poz., rys., tab., wykr.

Twórcy

autor

Cholewa M.

• University of Silesia, Institute of Computer Science, Będzińska 39, 41-200 Sosnowiec, Poland

autor

Palys M.

• University of Silesia, Institute of Computer Science, Będzińska 39, 41-200 Sosnowiec, Poland

Bibliografia

• [1] CHOLEWA M. Shannon information entropy as complexity metric of source code. 2017 MIXDES - 24th International Conference Mixed Design of Integrated Circuits and Systems, Bydgoszcz, 2017. pp. 468–471.
• [2] CZYŻ T., HAUKE J. Zastosowanie miary entropii do badania zmian w zróżnicowaniu regionalnym Polski. Rozwój Regionalny i Polityka Regionalna, 2015, Vol. 35. pp. 17–30.
• [3] DE ARRUDA P. F., GATTI M., FACIO JR. F. N., DE ARRUDA J. G., MOREIRA R. D., MURTA JR . L. O., DE ARRUDA L. F., DE GODOY M. F. Quantification of fractal dimension and Shannon’s entropy in histological diagnosis of prostate cancer. BMC Clinical Pathology, 2013, Vol. 13, No. 1.
• [4] EIMANN R. Network event detection with entropy measures. Ph. D. Thesis, University of Auckland, Auckland, New Zealand, 2008.
• [5] GULL S. F., SKILLING J. Maximum entropy method in image processing. IEE Proceedings, 1984, Vol. 131, No. 6. pp. 646–659.
• [6] KALOS M. H., WHITLOCK P. A. Monte Carlo methods. Wiley - VCH Verlag GmbH & Co. KGaA, 2008.
• [7] LIN J. Divergence measures based on the Shannon entropy. IEEE Transactions on information Theory, 1991, Vol. 37, No. 1. pp. 145–151.
• [8] RAHMAN S., RAHMAN M., ABDULLAH-AL-WADUD M., SCHOYAIB M. An adaptive gamma correction for image enhancement. EURASIP Journal on Image and Video Processing, 2016, Vol. 35, No. 1.
• [9] RAJALAXMI S., NIRMALA S. Entropy-based straight kernel filter for echocardiography image denoising. Journal of Digital Imaging, 2014, Vol. 27, No. 5. pp. 610–624.
• [10] SHANNON C. E. A mathematical theory of communication. Bell System Technical Journal, 1948, Vol. 27, No. 3. pp. 379–423.
• [11] SHLENS J. A light discussion and derivation of entropy. CoRR, 2014, Vol. abs/1401.1998.
• [12] WALLACE G. K. The JPEG still picture compression standard. IEEE Transactions on Consumer Electronics, 1992, Vol. 38, No. 1.
• [13] WĘDROWSKA E. Wykorzystanie entropii Shannona i jej uogólnień do badania rozkładu prawdopodobieństwa zmiennej losowej dyskretnej. Przegląd statystyczny, 2010, Vol. 57, No. 4.

Uwagi

PL

Opracowanie rekordu w ramach umowy 509/P-DUN/2018 ze środków MNiSW przeznaczonych na działalność upowszechniającą naukę (2018).