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LAPLACE

拉普拉斯(Pierre-SimonLAPLACE,1749－1827)是法國分析學(xué)家、概率論學(xué)家和物理學(xué)家，法國科學(xué)院院士。1749年3月23日生于法國西北部卡爾瓦多斯的博蒙昂諾日，1827年3月5日卒于巴黎。1816年被選為法蘭西學(xué)院院士，1817年任該院院長。1812年發(fā)表了重要的《概率分析理論》一書，在該書中總結(jié)了當(dāng)時整個概率論的研究，論述了概率在選舉審判調(diào)查、氣象等方面的應(yīng)用，導(dǎo)入「拉普拉斯變換」等。他是決定論的支持者，提出了拉普拉斯妖。他致力于挽救世襲制的沒落：他當(dāng)了六個星期的拿破侖的內(nèi)政部長，后來成為元老院的掌璽大臣，并在拿破侖皇帝時期和路易十八時期兩度獲頒爵位，后被選為法蘭西學(xué)院院長。拉普拉斯曾任拿破侖的老師，所以和拿破侖結(jié)下不解之緣。

Solutions are obtained for Poissson, diffusion, or wave PDEs homogeneous or nonhomogeneous equations

Solutions are obtained for Poissson, diffusion, or wave PDEs homogeneous or nonhomogeneous equations and/or boundary conditions rectangular, cylindrical, or spherical coordinates time, LAPLACE, or frequency domains Dirichlet, Neumann, Robin, singular, periodic, or incoming/outgoing boundary conditions. Output is suitable for pasting into LaTeX documents.

標(biāo)簽： nonhomogeneous homogeneous Solutions diffusion

上傳時間： 2015-10-30

上傳用戶：JasonC
Stochastic Geometry and Wireless Networks Volume I

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(biāo)簽： Stochastic Geometry Networks Wireless Volume and

上傳時間： 2020-06-01

上傳用戶：shancjb

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