CD Correlated Gaussian Random Noise VI
Owning Palette: Stochastic Systems VIs
Installed With: Control Design and Simulation Module
Generates a sample of one or two Gaussian-distributed random vectors, which you can use as the noise vectors w and v. You specify the mean, auto-covariance, and cross-covariance of these vectors. You must manually select the polymorphic instance to use.
Use this VI to generate values for the Process Noise w(k) and Measurement Noise v(k) inputs of the CD Discrete Stochastic State-Space function.
Use the pull-down menu to select an instance of this VI.
 Place on the block diagram | Find on the Functions palette |
CD Correlated Gaussian Random Noise (One Vector)
 | E{x} specifies the mean of the Gaussian random vector x. The length of E{x} determines the length of the random vector sample x and the dimensions of the Cov{x,x} matrix. | ||||||
 | Cov{x,x} specifies the covariance of the Gaussian-distributed random vector x. This covariance matrix can be either diagonal or non-diagonal, which means that samples of x can be uncorrelated or correlated with each other.
If n is the length of E{x}, the Cov{x,x} must be an n × n matrix. The Cov{x,x} matrix must be symmetric and positive semi-definite such that Cov{x,x} = Cov{x,x}T ≥ 0. | ||||||
 | error in describes error conditions that occur before this VI or function runs.
The default is no error. If an error occurred before this VI or function runs, the VI or function passes the error in value to error out. This VI or function runs normally only if no error occurred before this VI or function runs. If an error occurs while this VI or function runs, it runs normally and sets its own error status in error out. Use the Simple Error Handler or General Error Handler VIs to display the description of the error code.
Use exception control to treat what is normally an error as no error or to treat a warning as an error.
Use error in and error out to check errors and to specify execution order by wiring error out from one node to error in of the next node.
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 | random vector sample x returns a random sample of the Gaussian random vector x. The length of random vector sample x is equal to the length of the E{x} vector. | ||||||
 | error out contains error information. If error in indicates that an error occurred before this VI or function ran, error out contains the same error information. Otherwise, it describes the error status that this VI or function produces.
Right-click the error out front panel indicator and select Explain Error from the shortcut menu for more information about the error.
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CD Correlated Gaussian Random Noise (Two Vectors)
| E{x} specifies the mean of the Gaussian random vector x. The length of E{x} determines the length of the random vector sample x and the dimensions of the Cov{x,x} matrix. | ||||||
| E{y} specifies the mean of the Gaussian random vector y. The length of E{y} determines the length of the random vector sample y and the dimensions of the Cov{y,y}. | ||||||
| Cov{x,x} specifies the covariance of the Gaussian-distributed random vector x. This covariance matrix can be either diagonal or non-diagonal, which means that samples of x can be uncorrelated or correlated with each other.
If n is the length of E{x}, the Cov{x,x} must be an n × n matrix. The Cov{x,x} matrix must be symmetric and positive semi-definite such that Cov{x,x} = Cov{x,x}T ≥ 0. | ||||||
| Cov{y,y} specifies the covariance of the Gaussian-distributed random vector y. This covariance matrix can be either diagonal or non-diagonal, which means that samples of y can be uncorrelated or correlated with each other.
If m is the length of E{y}, the Cov{y,y} matrix must be an m × m matrix. The Cov{y,y} matrix must be symmetric and positive semi-definite such that Cov{y,y} = Cov{y,y}T ≥ 0. | ||||||
| error in describes error conditions that occur before this VI or function runs.
The default is no error. If an error occurred before this VI or function runs, the VI or function passes the error in value to error out. This VI or function runs normally only if no error occurred before this VI or function runs. If an error occurs while this VI or function runs, it runs normally and sets its own error status in error out. Use the Simple Error Handler or General Error Handler VIs to display the description of the error code.
Use exception control to treat what is normally an error as no error or to treat a warning as an error.
Use error in and error out to check errors and to specify execution order by wiring error out from one node to error in of the next node.
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| Cov{x,y} specifies the cross-covariance between the Gaussian random vectors x and y.
If n is the length of E{x} and m is the length of E{y}, the Cov{x,y} matrix must be an n × m matrix. The Cov{x,y} matrix also must satisfy the following relationship:  If you specify a matrix of zeros for the Cov{x,y} matrix, samples of the random vectors x and y are uncorrelated. | ||||||
| random vector sample x returns a random sample of the Gaussian random vector x. The length of random vector sample x is equal to the length of the E{x} vector. | ||||||
| random vector sample y returns a random sample of the Gaussian random vector y. The length of random vector sample y is equal to the length of the E{y} vector. | ||||||
| error out contains error information. If error in indicates that an error occurred before this VI or function ran, error out contains the same error information. Otherwise, it describes the error status that this VI or function produces.
Right-click the error out front panel indicator and select Explain Error from the shortcut menu for more information about the error.
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