BE-GY 6453 Probability and Stochastic Processes
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Students, under this BE-GY 6453 Probability and Stochastic Processes course will learn about continuous and discrete random variables and their joint probability distribution and density function; function of a random variable and its distribution; independent random variable and conditional distribution; the process contains:
- One and two random variables.
- Two parts of two random variables and their distribution Joint density function.
- Joint distributed discrete random variables and their functions.
- Characteristic functions and moments of higher orders.
- Covariance, correlation, orthogonality.
- Collective Gaussian random variables.
- Linear functions of Gaussian random variables and their joint density functions.
The concept of a random process and stationarity; strictly fixed (SSS) and widely selected (WSS) processes; autocorrelation function and its properties; Poisson process and Wiener process; linear time-invariant (LTI) system; random entry and its autocorrelation of entry and exit; input and output power spectrum of a linear system with a random input; minimum mean square error (MMSE) estimate and orthogonality principle; the autoregressive moving average (ARMA) process and its power spectrum are studied under this course.
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