将u=代入arshu=-(ny+lnC)后的整理过程:

The signal suffers an attenuation loss l Received power PR= PT/L Received snr=E,/No, Eb=Pr/Rb Antennas are used to compensate for attenuation loss Capture as much of the signal as possible

一、马尔可夫过程当随机过程在t所处的状态为已知条件时,过程 在时刻ttr所处的状态仅与tx时的状态有关,而与t以前的状态无关,这 种随机过程为马尔可夫过程。 用分布函数来描述:若在条件Y(t)=(i1,2n)下的Y的分布函数恰 好等于条件Y(tn-=Yn-1下的分布函数,即 FYn; t, Yn-I Yn-... Y In-1 n-2..) =F(Yn; t, Yn-1; tn-1) 则称Y(t)为马尔可夫过程

6=e.e e.×e Eiker j Vφ 随体倒数Dn-ar +(V)a a e Vxa=(e.)x(a e)=e

1.拉格朗日变数(a,b,c)给出的流体运动规律为x=ae,y=b(1+1) z=ce(1+t) -2 l)求以欧拉变数描述的速度场;

Information content of a random variable Random variable x Outcome of a random experiment Discrete R V takes on values from a finite set of possible outcomes PMF: P(X=y)=Py) How much information is contained in the event X=y? Will the sun rise today Revealing the outcome of this experiment provides no information Will the Celtics win the NBa championship? Since this is unlikely, revealing yes provides more information than revealing Events that are less likely contain more information than likely events

在现代经济管理中,有许多最优化问题属于多元函 数的极值和最值问题同一元函数类似,其最值也与其极 值有十分密切的联系;故以下以二元函数为例用多元函 数微分法先来讨论多元函数的极值,再讨论多元函数的 最值. 多元函数极值问题有两种基本类型(以二元函数为例) 类型I:讨论z=f(xy)的极值——无条件极值 类型Ⅱ:讨论z=f(xy)在约束条件(xy)=0下的极值 条件极值

Testing for AR(IS eria Correlation Want to be able to test for whether the errors are serially correlated or not Want to test the null thatp=0 in u,=pu, 1 +et=2.. where u is the model error

简要证明仅就uvn(n=1,2,…)的情形证明 设级数v收敛,其和为,则级数un的部分和 S=u1+u2++unv1+v2+…+vno(n=1,2,), 即部分和数列{sn}有界.因此级数un收敛 反之,若级数un发散,则级数∑v,必发散.这是因为如果 级数∑v收敛,由已证结论,级数un也收敛,矛盾

高斯公式:=Pdydz+dx+ Rdxdy. 简要证明设Ω是一柱体,下边界曲面为1:z=z1(x,y),上 边界曲面为2:=2(x,y),侧面为柱面3;Σ1取下侧,Σ2取上侧, Σ3取外侧. 根据三重积分的计算和对坐标的曲面积分的计算得