Please use this identifier to cite or link to this item: http://hdl.handle.net/11455/8920
標題: 含雜訊干擾的基因網路強健估測器設計
Robust Estimator Design for Noisy Gene Networks
作者: 莊佳華
Chuang, Chia-Hua
關鍵字: biological system;生物系統;gene network;stochastic model;extended Kalman filter;stability analysis;基因網路;隨機模型;擴展型卡曼濾波器;穩定性分析
出版社: 電機工程學系所
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摘要: 
生物系統中的基因網路牽涉許多交換訊息和回授調整機制以及須忍受來自本質變動引發的分子雜訊、來自逆流基因的傳遞雜訊和影響到所有的基因的總合雜訊,因而具有高度非線性與隨機性。在這種環境下,如何藉控制策略和生物技術來濾除雜訊,量測出雜訊干擾下的內部狀態,對控制工程師與生物學家來說是非常具有吸引力的問題。然而,生物系統的內部狀態往往無法直接得到,本論文中,針對存有雜訊不確定性的基因網路提出利用強健擴展型卡曼濾波器來進行狀態估測和濾除雜訊,並應用李亞普諾夫穩定理論進行估測性能的量化分析並且對於幾個實際的基因網路進行模擬驗證。希望本研究發展的理論對未來基因網路的研究發展有正面的助益。

Gene networks in biological systems are highly complicated due to nonlinear and stochastic features that they involve many crosstalk and feedback regulatory mechanisms and may be suffered from noise corruption due to the molecular noises from intrinsic fluctuations, transmitted noise from upstream genes, and the global noise affecting all genes. In this environment, how to filter noises and measure the internal states of noisy gene networks by systematic control strategies and biological techniques are attractive issues to control engineers and biologists. However, the internal states of most biological systems might not be directly accessible. In this thesis, a robust extended Kalman filter for state estimation of a class of noisy nonlinear gene networks with uncertain process noise and multiple noises is presented. Quantitative analysis of the estimation performance based on Lyapunov stability theory is conducted. Numerical simulations for real gene networks are provided to effectively confirm the proposed method.
URI: http://hdl.handle.net/11455/8920
其他識別: U0005-2308201013210400
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