SDELab 解隨機微分方程的一個Matlab工具包 A package for solving stochastic differential equations in MATLAB
標簽： differential stochastic equations package
上傳時間： 2013-12-19
上傳用戶：er1219
A stochastic Parts Program and Noun Phrase Parser for Unrestricted Text
標簽： Unrestricted stochastic Program Parser
上傳時間： 2013-12-29
上傳用戶：lhw888
java Labyrinth game；Provides two kinds to produce map s way stochastically: The stochastic distribution point method and the chart depth first traversal the law two kinds.It can searches the shortest way to demonstrate automatically
標簽： stochastically stochastic Labyrinth distribut
上傳時間： 2016-06-13
上傳用戶：qilin
一種基于概率的數據降維處理方法：stochastic Neighbor Embedding
標簽： stochastic Embedding Neighbor 概率
上傳時間： 2016-11-27
上傳用戶：yan2267246
A stochastic Time-to-Digital Converter for Digital Phase-Locked Loops
標簽： Time-to-Digital Phase-Locked stochastic Converter
上傳時間： 2014-01-16
上傳用戶：ANRAN
SIMULATION AND ESTIMATION OF stochastic DIFFERENTIAL EQUATIONS WITH MATLAB
標簽： DIFFERENTIAL SIMULATION ESTIMATION stochastic
上傳時間： 2017-01-18
上傳用戶：宋桃子
Solving stochastic Differential Equations with Maple By Sasha Cyganowski
標簽： Differential Cyganowski stochastic Equations
上傳時間： 2017-03-02
上傳用戶：qq1604324866
Designing delivery districts for the vehicle routing problem with stochastic demands
標簽： stochastic Designing districts delivery
上傳時間： 2013-12-13
上傳用戶：大三三
stochastic diff equ, 隨即微分方程的,比較使用
標簽： stochastic diff equ 微分方程
上傳時間： 2017-07-24
上傳用戶：Thuan
Part I provides a compact survey on classical stochastic geometry models. The basic models defined in this part will be used and extended throughout the whole monograph, and in particular to SINR based models. Note however that these classical stochastic models can be used in a variety of contexts which go far beyond the modeling of wireless networks. Chapter 1 reviews the definition and basic properties of Poisson point processes in Euclidean space. We review key operations on Poisson point processes (thinning, superposition, displacement) as well as key formulas like Campbell’s formula. Chapter 2 is focused on properties of the spatial shot-noise process: its continuity properties, its Laplace transform, its moments etc. Both additive and max shot-noise processes are studied. Chapter 3 bears on coverage processes, and in particular on the Boolean model. Its basic coverage characteristics are reviewed. We also give a brief account of its percolation properties. Chapter 4 studies random tessellations; the main focus is on Poisson–Voronoi tessellations and cells. We also discuss various random objects associated with bivariate point processes such as the set of points of the first point process that fall in a Voronoi cell w.r.t. the second point process.
標簽： stochastic Geometry Networks Wireless Volume and
上傳時間： 2020-06-01
上傳用戶：shancjb
