Search results for: BAYESIAN TRACKING - Bridge of Knowledge

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Search results for: BAYESIAN TRACKING
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Search results for: BAYESIAN TRACKING

  • On Bayesian Tracking and Prediction of Radar Cross Section

    We consider the problem of Bayesian tracking of radar cross section. The adopted observation model employs the gamma family, which covers all Swerling cases in a unified framework. State dynamics are modeled using a nonstationary autoregressive gamma process. The principal component of the proposed solution is a nontrivial gamma approximation, applied during the time update recursion. The superior performance of the proposed approach...

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  • Bayesian Analysis

    Journals

    ISSN: 1931-6690 , eISSN: 1936-0975

  • Direct spectrum detection based on Bayesian approach

    The paper investigates the Bayesian framework's performance for a direct detection of spectrum parameters from the compressive measurements. The reconstruction signal stage is eliminated in by the Bayesian Compressive Sensing algorithm, which causes that the computational complexity and processing time are extremely reduced. The computational efficiency of the presented procedure is significantly...

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  • Application of Bayesian Networks for Forecasting Future Model of Farm

    Publication

    - Agricultural Engineering - Year 2017

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  • Observation value analysis - integral part of Bayesian diagnostics

    Publication

    Detailed subject of the research is to analyse the value of the observation, which is a part of preposterior analysis. For the presented network, the main objective was to determine, conducting of which of three tests is the most valuable from the perspective of determining possible need or possibility to omission expensive technical expertise. The main advantage of preposterior analysis is answering the question which of the considered...

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  • Dynamic Bayesian Networks for Symbolic Polyphonic Pitch Modeling

    Publication

    Symbolic pitch modeling is a way of incorporating knowledge about relations between pitches into the process of an- alyzing musical information or signals. In this paper, we propose a family of probabilistic symbolic polyphonic pitch models, which account for both the “horizontal” and the “vertical” pitch struc- ture. These models are formulated as linear or log-linear interpo- lations of up to fi ve sub-models, each of which is...

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  • Observation Value Analysis – Integral Part of Bayesian Diagnostics

    The decision making process, in general, is understood as a process of selecting one of the available solutions to the problem. One of possible approaches supporting the process is Bayesian statistical decision theory providing a mathematical model to make decisions of a technical nature in conditions of uncertainty. Regarding above, a detailed subject of the research is to analyze the value of the observation, which is a part...

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  • Target tracking in RIS

    Publication
    • W. Kazimierski
    • A. Stateczny

    - Year 2009

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  • Bayesian estimation of the parameters in safely and reliability models for the subjective priors.

    Publication

    - Year 2003

    Rozważono problem estymacji nieznanych charakterystyk niezawodnościowych za pomocą nieparametrycznych metod Bayesowskich. W wielu przypadkach opinie ekspertów są jedynym źródłem danych apriorycznych w modelach Bayesowskich. Celem uzyskania subiektywnych prawdopodobieństw apriorycznych zastosowano pewne metody ekspertowe. W oparciu o proces Dirichleta, który jest kluczowym pojęciem w teorii Fergusona, zostały skonstruowane...

  • A Bayesian regularization-backpropagation neural network model for peeling computations

    Publication
    • S. Gouravaraju
    • J. Narayan
    • R. Sauer
    • S. S. Gautam

    - JOURNAL OF ADHESION - Year 2023

    A Bayesian regularization-backpropagation neural network (BRBPNN) model is employed to predict some aspects of the gecko spatula peeling, viz. the variation of the maximum normal and tangential pull-off forces and the resultant force angle at detachment with the peeling angle. K-fold cross validation is used to improve the effectiveness of the model. The input data is taken from finite element (FE) peeling results. The neural network...

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