Radial point collocation method for solving fpk equation in stochastic dynamics 方程的徑向基點插配點方法求解
Stability analysis for stochastic dynamic traffic assignment models 動態(tài)交通分配與信號控制的組合模型及算法研究
We start by covering deterministic and stochastic dynamic optimization using dynamic programming analysis 我們會以使用動態(tài)規(guī)劃分析來處理確定及隨機的動態(tài)最適化作為開始。
Based on the recent situation and trend of the nonlinear systems, we present some recent developments and important problems in stochastic dynamics such as response, bifurcation, chaos, synchronization and control 摘要介紹了非線性隨機動力學的響應、分岔、混沌以及混沌同步與控制的研究現(xiàn)狀和發(fā)展趨勢,探討了隨機復動力系統(tǒng)、時滯系統(tǒng)、逼近方法和數值方法研究中的若干問題及其進展。
Markov decision process, in short mdp, is also called sequential stochastic optimization stochastic optimum control . the controlled markov process or stochastic dynamic programming is the theory on stochastic sequential decision 馬爾可夫決策過程(markovdecisionprocesses,簡稱mdp,又稱序貫隨機最優(yōu)化、隨機最優(yōu)控制、受控的馬爾可夫過程或隨機動態(tài)規(guī)劃)是研究隨機序貫決策的問題的理論。
In continuous-lime framework, assuming that asset price follows stochastic diffusion process, it introduces parametric uncertainty, and applies stochastic dynamic programming to derive the closed-form solution of optimal portfolio choice, which maximizes the expected power utility of investor's terminal wealth; in discrete-time framework, continuous compounding monthly returns of risky asset are assumed to be normal i . 1 . d ., it applies the rule of bayesian learning to do empirical study about two different sample of shanghai exchange composite index 在連續(xù)時間下假設資產的價格服從隨機擴散過程,引入參數不確定性,利用隨機動態(tài)規(guī)劃方法推導出風險資產最優(yōu)配置的封閉解,使投資者的終期財富期望冪效用最大;在離散時間下假設風險資產的連續(xù)復合月收益率服從獨立同分布的正態(tài)分布,通過貝葉斯學習準則,以上證綜合指數不同區(qū)間段的兩個樣本做實證研究。
But to this algorithm, it is important to select initial value and the amount of computation is large; ( 3 ) an algorithm is presented to estimate the prfs based on stochastic dynamic-linear models . ( 4 ) a new algorithm for selecting detecting threshold based on the wavelet theory is presented to the environment when pulse sequences distribute unevenly in the whole sampling time 該算法的不足是對初始狀態(tài)的選取非常重要且運算量較大;(3)提出基于動態(tài)線性模型利用prf進行重頻分選的算法;(4)將小波理論應用到重頻分選中,提出了一種新的檢測門限,適用于脈沖列分布不均勻的信號環(huán)境。
In this thesis improved algorithms are presented as follows : ( 1 ) an algorithm based on the detection of arithmetical series is presented to deinterleave radar signals with stagger pris, especially to those with high order stagger ones . but this algorithm is limited to the model of stagger pri presented by resnick; ( 2 ) an algorithm is presented to estimate the pris of radar signals with jittered pris based on stochastic dynamic-linear models . this algorithm fits radar signals with jittered pris well, especially when jittered amount is large 針對這種情況,本文提出了以下改進的重頻分選算法:(1)針對參差pri脈沖列提出一種重頻分選算法,該算法使用等差數列的檢測進行參差鑒別,非常適于對高參差雷達脈沖列的分選,但只局限于雷斯尼克提出的參差模型;(2)針對抖動pri脈沖列提出基于動態(tài)線性模型的重頻分選算法,非常適用于抖動量較大的情況。
As for the issues of non-traded assets, applying the approach of stochastic dynamic programming, and under the principle of no-arbitrage, we obtain optimal strategy to hedge the real option in discrete and continuous conditions . and to the problems of special distribution of underlying assets, this paper analyzes the price movement of the underlying assets from the arrival of information, the market efficiency and the market mechanism which decide the price 對實物資產的特殊價值分布問題,本文從決定資產價格的市場機制、信息到達方式及市場效率三方面來分析實物資產的價格變動特征;并重點研究當基本資產遵循純跳躍poisson過程、跳躍擴散merton過程及均值回復過程時的實物期權定價問題,運用復制定價和隨機動態(tài)規(guī)劃方法,得到確定實物期權價值和風險對沖策略的偏微分方程。
Many investigations show that randomicity of structures ? parameter will bring large value of stochastic dynamic response of structures . randomicity of structures ? mechanics parameter may be dominant factors . therefore, introduction of randomicity into system model of structure and using random system model are more reasonable than that of determinate system model 眾多的研究工作表明,結構參數的隨機變異性可以引起結構隨機動力響應的大幅度漲落,結構力學參數的隨機性還可能成為主導因素,在結構系統(tǒng)模型中引入隨機性的概念,采用隨機結構系統(tǒng)模型是較確定性結構系統(tǒng)模型更為合理的一種選擇。