25-26-1-随机信号分析-期末 目录 四、(13 分) 四、(13 分) X(t)X(t)X(t) 为平稳正态随机过程,功率谱 GX(ω)=5ω2+8ω4+5ω2+4G_{X}(\omega)=\frac{5 \omega^{2}+8}{\omega^{4}+5 \omega^{2}+4}GX(ω)=ω4+5ω2+45ω2+8, Y(t)=X(t−t0)+1Y(t) = X\left(t - t_{0}\right) + 1Y(t)=X(t−t0)+1。求: X(t)X(t)X(t) 的自相关函数和均值。(已知 e−α∣τ∣↔2αω2+α2\mathrm{e}^{-\alpha |\tau|} \leftrightarrow \frac{2\alpha}{\omega^2 + \alpha^2}e−α∣τ∣↔ω2+α22α)(5 分) › 答案 / 解析 GX(ω)=12⋅2×1ω2+12+2×2ω2+22G_X(\omega) = \frac{1}{2} \cdot \frac{2 \times 1}{\omega^2 + 1^2} + \frac{2 \times 2}{\omega^2 + 2^2}GX(ω)=21⋅ω2+122×1+ω2+222×2 (2 分)RX(τ)=12e−∣τ∣+e−2∣τ∣R_X(\tau) = \frac{1}{2}\mathrm{e}^{-|\tau|} + \mathrm{e}^{-2|\tau|}RX(τ)=21e−∣τ∣+e−2∣τ∣ (1 分)mX2=RX(∞)m_X^2 = R_X(\infty)mX2=RX(∞) (1 分) =0 ⟹ mX=0= 0 \implies m_X = 0=0⟹mX=0 (1 分) Y(t)Y(t)Y(t) 的自相关函数。(3 分) › 答案 / 解析 RY(τ)=E[Y(t+τ)Y(t)2]=E{[X(t+τ−t0)+1][X(t−t0)+1]2}=RX(τ)+2mX+1=12e−∣τ∣+e−2∣τ∣+1\begin{align*} R_Y(\tau)=&E[Y(t+\tau)Y(t)^2]=E\{[X(t+\tau-t_0)+1][X(t-t_0)+1]^2\}\\ =&R_X(\tau)+2m_X+1\tag{2分}\\ =&\frac12\mathrm e^{-|\tau|}+\mathrm e^{-2|\tau|}+1\tag{1分} \end{align*}RY(τ)===E[Y(t+τ)Y(t)2]=E{[X(t+τ−t0)+1][X(t−t0)+1]2}RX(τ)+2mX+121e−∣τ∣+e−2∣τ∣+1(2分)(1分) Y(t)Y(t)Y(t) 的均值、方差及一维概率密度。(5 分) › 答案 / 解析 mY=E[X(t−t0)+1]2=mX+1=1m_Y = E\left[ X\left(t-t_0\right) + 1 \right]^2 = m_X + 1 = 1mY=E[X(t−t0)+1]2=mX+1=1 (1 分)σY2=RY(0)−mY2=(12+1+1)−12=32\begin{align*} \sigma_Y^2=&R_Y(0)-m_Y^2\tag{1分}\\ =&(\frac12+1+1)-1^2=\frac32\tag{1分} \end{align*}σY2==RY(0)−mY2(21+1+1)−12=23(1分)(1分)Y(t)Y(t)Y(t) 服从正态分布fY(y)=12π⋅32exp(−(y−1)22⋅32)=13πexp(−(y−1)23)\begin{align*} f_Y(y) =& \frac{1}{\sqrt{2\pi \cdot \frac{3}{2}}} \exp\left( -\frac{(y-1)^2}{2 \cdot \frac{3}{2}} \right) \\ =& \frac{1}{\sqrt{3\pi}} \exp\left( -\frac{(y-1)^2}{3} \right) \end{align*}fY(y)==2π⋅231exp(−2⋅23(y−1)2)3π1exp(−3(y−1)2)(2 分)