stochastic filtering 中文意思是什麼
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Real time seafloor tracking technique is the critical technique to ensure smooth seafloor surveying with full coverage and high efficiency. after detailed investigation on stochastic features of seabed reverberation produced by mbss systems, the author presented an algorithm and a set of relevant key coefficients for real time seafloor tracking, taking into account of characteristics of signal processing and timing sequence of the real system and introducing theorems of terrain surveying. as an achievement, a mathematical model was established based on the technique of centered filtering
海底地形實時跟蹤技術是保證多波束測深系統實現高效率全覆蓋水下地形測量的核心技術，作者通過對多波束測深系統海底回波信號統計特性的研究，依據地形測量理論，並結合實際系統信號處理的技術特點和處理時序，提出了實現海底跟蹤控制的關鍵參數及計算方法，建立了基於中值濾波技術的海底地形實時跟蹤數學模型，並開發出實時地形跟蹤專家系統，該系統經多次海上實驗驗證表明：理論正確、方案可行，取得良好效果。 -
Therefore, basic methodologies for stochastic seismic and filtering responses of nonlinear structure are studied, the approximate solution methodologies and their practical applications are investigated in the dissertation employing equivalent linearization and moment equations method based on fpk equations and ito stochastic differential equations
因此，本文基於fpk方程和伊藤隨機微分方程，研究了滯后結構物的隨機地震反應和隨機濾波問題的基本方法，並利用等效線性化法和矩方程法，研究了非線性結構隨機地震反應分析和隨機濾波分析的近似解法及它們的工程應用。 -
The deducing of the algorithms has very practical value in state estimation for systems under the complex environments. in the instance of complicated multi - channel system with multiplicative noise, the dissertation discusses the optimal estimation of state filtering and smoothing and the stochastic input signal with the technique of innovation and projection theorem of hilbert space. the main study of the dissertation is introduced as follows : 1 according to the practical requirement of complicated multi - channel system with multiplicative noise, the dissertation broadens rajasekaran filtering algorithm
本文針對復雜多通道帶乘性噪聲系統，應用新息的方法和hilbert空間的投影定理，對狀態最優濾波和平滑估計、隨機輸入信號的最優估計等理論與應用方面的問題，進行了進一步的探討，著重完成了以下工作：第一，根據復雜多通道乘性噪聲系統問題的實際需要，推廣了rajasekaran濾波演算法。 -
Since there are a lot of periodic non - stationary stochastic processes, i combine the kalman filtering and multiresolution analysis methods, and propose the wavelet - kalman filtering hybrid estimating and forecasting method. this method has the real - time, recursion and multiresolution characteristics. in this paper, using this method, i realize the real - time tracking and dynamic multistep forecasting in one cycle
針對自然、社會和經濟等環境中存在有大量周期性的非平穩隨機過程，我們將kf方法和多尺度分析方法相結合，提出了既具有實時性和遞歸性又具有多尺度分析能力的小波?卡爾曼濾波混合估計與預報方法，應用此方法可實現周期內對目標狀態的實時跟蹤估計和動態多步預報。 -
Kalman filtering is widely used for data processing in kinematic gps positioning, while the practical application of kalman filtering requires the dynamic model ( functional model ) and the stochastic model to be reliable and accurate, yet it is difficult to maintain regular motion of the object in actual kinematic positioning, thus model biases are usually generated
摘要動態定位的數據處理中廣泛應用卡爾曼濾波，而卡爾曼濾波的應用要求動態模型（函數模型）和隨機模型可靠和切合實際，但實際測量定位中難以保證觀測對象的規則運動，因而容易出現模型誤差。 -
Combining forward and backward stochastic differential equations and filtering techniques, the nash equilibrium point of a type of partially observed lq nonzero sum stochastic differential game problem is obtained
摘要結合正倒向隨機微分方程理論和濾波技術，給出了一類部分可觀測信息下線性二次非零和隨機微分對策問題的納什均衡點。
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