Do you want BuboFlash to help you learning these things? Or do you want to add or correct something? Click here to log in or create user.


  • Presentation
  • Question
  • Answer

Question
For any random process \(X_{t}\), the Autocorrelation at time instants \(t_{1}\) and \(t_{2}\) is: [...]
Answer

\(\displaystyle\mathbf{E}[X_{t_{1}}X_{t_{2}}]=\int_{\Omega}X_{t_{1}}(\alpha)X_{t_{2}}(\alpha)P(d\alpha)=\int_{\mathbb{R}^{2}}x_{1}x_{2}\mu_{t_{1}t_{2}}(dx_{1}\times dx_{2})\)

where \(\mu_{t_{1}t_{2}}(dx_{1}\times dx_{2})\) is a joint probability distribution.


Question
For any random process \(X_{t}\), the Autocorrelation at time instants \(t_{1}\) and \(t_{2}\) is: [...]
Answer
?

Question
For any random process \(X_{t}\), the Autocorrelation at time instants \(t_{1}\) and \(t_{2}\) is: [...]
Answer

\(\displaystyle\mathbf{E}[X_{t_{1}}X_{t_{2}}]=\int_{\Omega}X_{t_{1}}(\alpha)X_{t_{2}}(\alpha)P(d\alpha)=\int_{\mathbb{R}^{2}}x_{1}x_{2}\mu_{t_{1}t_{2}}(dx_{1}\times dx_{2})\)

where \(\mu_{t_{1}t_{2}}(dx_{1}\times dx_{2})\) is a joint probability distribution.

If you want to change selection, open document below and click on "Move attachment"

随机过程的自相关函数
For any random process \(X_{t}\), the Autocorrelation at time instants \(t_{1}\) and \(t_{2}\) is: \(\displaystyle\mathbf{E}[X_{t_{1}}X_{t_{2}}]=\int_{\Omega}X_{t_{1}}(\alpha)X_{t_{2}}(\alpha)P(d\alpha)=\int_{\mathbb{R}^{2}}x_{1}x_{2}\mu_{t_{1}t_{2}}(dx_{1}\times dx_{2})\) where \(\mu_{t_{1}t_{2}}(dx_{1}\times dx_{2})\) is a joint probability distribution.

Summary

statusnot learnedmeasured difficulty37% [default]last interval [days]               
repetition number in this series0memorised on               scheduled repetition               
scheduled repetition interval               last repetition or drill

Details

No repetitions

Discussion

Do you want to join discussion? Click here to log in or create user.