Reconstruction of high-dimensional data using the method of probabilistic features combination

• Autorzy: Jakóbczak D. J.
• Języki publikacji: EN

Abstrakty

EN

Proposed method, called Probabilistic Features Combination (PFC), is the method of multi-dimensional data modeling, extrapolation and interpolation using the set of high-dimensional feature vectors. This method is a hybridization of numerical methods and probabilistic methods. Identification of faces or fingerprints need modeling and each model of the pattern is built by a choice of multi-dimensional probability distribution function and feature combination. PFC modeling via nodes combination and parameter γ as N-dimensional probability distribution function enables data parameterization and interpolation for feature vectors. Multidimensional data is modeled and interpolated via nodes combination and different functions as probability distribution functions for each feature treated as random variable: polynomial, sine, cosine, tangent, cotangent, logarithm, exponent, arc sin, arc cos, arc tan, arc cot or power function.

PL

Autorska metoda Probabilistycznej Kombinacji Cech - Probabilistic Features Combination (PFC) jest wykorzystywana do interpolacji i modelowania wielowymiarowych danych. Węzły traktowane są jako punkty charakterystyczne N-wymiarowej informacji, która ma być odtwarzana (np. obraz). Wielowymiarowe dane są interpolowane lub rekonstruowane z wykorzystaniem funkcji rozkładu prawdopodobieństwa: potęgowych, wielomianowych, wykładniczych, logarytmicznych, trygonometrycznych, cyklometrycznych.

Słowa kluczowe

EN

image retrieval; pattern recognition; data modeling; vector interpolation; PFC method; feature reconstruction; probabilistic modeling

PL

pobieranie obrazu; rozpoznawanie wzorców; modelowanie danych; interpolacja wektora; metoda PFC; funkcja rekonstrukcji; modelowanie probabilistyczne

• Wydawca: Wydawnictwo Uczelniane Politechniki Koszalińskiej
• Czasopismo: Zeszyty Naukowe Wydziału Elektroniki i Informatyki Politechniki Koszalińskiej
• Rocznik: 2016
• Tom: Nr 9
• Strony: 37--50
• Opis fizyczny: Bibliogr. 26 poz., rys., wykr.

Twórcy

autor

Jakóbczak D. J.

• Zakład Podstaw Informatyki i Zarządzania, Wydział Elektroniki i Informatyki, Politechnika Koszalińska

Bibliografia

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• 25. Schumaker, L.L.: Spline Functions: Basic Theory. Cambridge Mathematical Library (2007)
• 26. Jakóbczak, D.J.: 2D Curve Modeling via the Method of Probabilistic Nodes Combination - Shape Representation, Object Modeling and Curve Interpolation-Extrapolation with the Applications. LAP Lambert Academic Publishing,Saarbrucken (2014)