- stochastic or random variable x가 로 불리는 k중의 하나를 특별하게 취할 수 있다면, discrete-valued 라고 말한다.
-확률분포는 각각의 확률결과가 주어진 일련의 수들이다.
- x가 을 취한 확률.
-확률의 합은 1 ▪
-로 실행할 수 있는 결과를 요구하면. X가 값과 동일하거나 더 적은 값을 취한 확률이 다음과 같이 주어진다.
▪
- X가 확률 1인 constant c 와 동일하다면, ➜ X는 nonstochastic.
-continuous -valued random variable X 에 대한 확률규칙은
▪인 밀도함수 로 서술.
-의 X는 random variable X의 밀도라는 것 의미.
-의 독립변수 x는 위식에서 적분의 지수를 의미.
-를 의미하는, X의 중복 분포함수는, X가 a보다 적거나 동일한 값을 취한 확률을 산출한다.
▪
2.probability density function of a continuous random variable.
∙X는 연속확률변수.
⇒ 는 연속확률밀도함수.
3.joint probability density functions.
∙ X와 Y는 2개의 이산확률변수.
⇒이산결합 확률밀도함수.
-결합밀도 인 두 개의 random variable X와 Y에 대해 다음식을 통해
인 joint event (결합사건)의 확률을 계산.
▪
-결합누적분포함수는 .
▪
-자체적으로 인 확률은 다음식에서 계산.
▪
-와 위식을 비교, marginal density 는 결합밀도를 y에 관해 적분함으로써 얻어진다는 것을 알수 있다.
▪ ➜
Random Processes and Stochastic System Random Processes and Stochastic System
2008. 10. 2
3. Random Processes and Stochastic System
3.1 Chapter Focus
3.1.1 Discovery and Modeling of Random Process
3.1.2 Main Points to Be Covered
3.1.3..
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