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Search results for: KERNEL PCA
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Kernel PCA in Application to Leakage Detection in Drinking Water Distribution System
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Kernel PCA in Application to Leakage Detection in Drinking Water Distribution System
PublicationMonitoring plays an important role in advanced control of complex dynamic systems. Precise information about system's behaviour, including faults detection, enables efficient control. Proposed method- Kernel Principal Component Analysis (KPCA), a representative of machine learning, skilfully takes full advantage of the well known PCA method and extends its application to nonlinear case. The paper explains the general idea of KPCA...
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Data-driven models for fault detection using kernel PCA: A water distribution system case study
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Optimising approach to designing kernel PCA model for diagnosis purposes with and without a priori known data reflecting faulty states
PublicationFault detection plays an important role in advanced control of complex dynamic systems since precise information about system condition enables efficient control. Data driven methods of fault detection give the chance to monitor the plant state purely based on gathered measurements. However, they especially nonlinear, still suffer from a lack of efficient and effective learning methods. In this paper we propose the two stages learning...
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Representation of the Poisson kernel for Jacobi and Hahn polynomials
PublicationW pracy przedstawiono dowód twierdzenia o reprezentacji jąder Poissona dla wielomianów Jacobiego wypukłą kombinacją nieujemnych jąder typu Durrmeyera. Podobne rezultaty uzyskano dla jąder Poissona dla dyskretnych wielomianów Hahna.
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On asymptotic periodicity of kernel double Markovian operators
PublicationIt is proved that a kernel, doubly Markovian operator T is asymptotically periodic if and only if its deterministic σ-field Σd(T)(equivalently Σd(T∗)) is finite. It follows that kernel doubly Markovian operator T is asymptotically periodic if and only if T∗ is asymptotically periodic.
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Endoscopy images classification with kernel based learning algorithms.
PublicationPrzedstawiono zastosowanie algorytmów opartych na wektorach wspierających zbudowanych na dwóch różnych funkcjach straty do klasyfikacji obrazów endoskopowych przełyku. Szczegółowo omówiono sposób ekstrakcji cech obrazów oraz algorytm klasyfikacji. Klasyfikator został zastosowany do problemu rozpoznawania zdjęć guzów złośliwych i łagodnych.
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CERNE
Journals -
PCA based Fault Tolerant MPC
PublicationThis chapter presents a Fault Tolerant - Model Predictive Control (FT-MPC) schemes for sensor faults accommodation. A Fault Detection and Isolation (FDI) Unit, which is an integral part of FT-MPC system, is based on the Principal Component Analysis (PCA) method. Introduced approach enables efficient bias and drift faults accommodation in single, as well as simultaneous faults case. Simple simulation exercise is presented.Rozdział...
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Flame retardant effect and mechanism of nanosized NiO as synergist in PLA/APP/CSi-MCA composites
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