Back to the 2024 paper

Module 3: Probability & Random Processes

20247m

Explain the concept of probability density function (PDF) and cumulative distribution function (CDF) in random processes.

Worked SolutionAI Assisted

Answer

PDF fX(x)f_X(x): P(x<X≤x+dx)=fX(x)dxP(x<X\le x+dx)=f_X(x)dx, ∫f=1\int f=1, FX(x)=∫−∞xfF_X(x)=\int_{-\infty}^x f. CDF FX(x)=P(X≤x)F_X(x)=P(X\le x): monotonic 0→1, f=dF/dxf=dF/dx. Gaussian f=(1/2πσ)e−(x−μ)2/2σ2f=(1/\sqrt{2\pi}\sigma)e^{-(x-\mu)^2/2\sigma^2}, F=Φ((x−μ)/σ)F=\Phi((x-\mu)/\sigma). Use for BER via QQ.

Similar questions

Student FinanceWeb Platform

Pocketly — Personal Finance for Students

Keep your hostel and college expenses under control. Track accounts, log spending in seconds, and stay within your monthly budget.