ContinuousRandom
This block is a continuous random wave generator. Each output component takes piecewise constant random values. Each time an event is received on the block input activation port, the outputs take new independent random values. The output port size is given by the size of the parameter matrices. You can select the distribution.
Library
SignalGenerators
Description
The ContinuousRandom block is a continuous random wave generator. Each output component takes piecewise constant random values. Every time an event is received on the input event port, the outputs take new independent random values. Output port size is given by the size of the parameters matrices. You can choose the distribution.
Supported distributions are: Uniform, Normal, Lognormal, Beta, Gamma, Chi-squared, Exponential, F, T, Pearson I, Pearson III, Pearson V, Pearson VII, Inverse Gamma, Inverse Beta.
Parameters
| Name | Label | Description | Data Type | Valid Values |
|---|---|---|---|---|
distrib | Select a distribution : | Probability distribution. Default value: 'uniform'. | Structure | |
distrib/uniform | Uniform | Number | 0 | |
distrib/normal | Standard Normal | Number | 0 | |
distrib/log_normal | Log-Normal | Number | 0 | |
distrib/beta | Beta | Number | 0 | |
distrib/gamma | Gamma | Number | 0 | |
distrib/chi | Chi-squared | Number | 0 | |
distrib/exp | Exponential | Number | 0 | |
distrib/F | F-distribution | Number | 0 | |
distrib/T | T-distribution | Number | 0 | |
distrib/pearson | Pearson | Number | 0 | |
distrib/inv_gamma | Inverse Gamma | Number | 0 | |
distrib/inv_beta | Inverse Beta | Number | 0 | |
seed | Seed (-1 for automatic) | Seed for the random generator (scalar). seed must be an integer between 0 and 2^32-1. Negative value for seed means automatic selection. | Matrix | |
Uniform_param | Uniform distribution parameters | Uniform probability distribution parameters. | Structure | |
Uniform_param/A | Lower bound | Cell of matrices | ||
Uniform_param/B | Upper bound | Cell of matrices | ||
Normal_param | Normal distribution parameters | Standard normal probability distribution parameters. | Structure | |
Normal_param/mean | Mean | Cell of matrices | ||
Normal_param/variance | Standard deviation (>0) | Cell of matrices | ||
LNormal_param | Log-Normal distribution parameters | Log-Normal probability distribution parameters. | Structure | |
LNormal_param/meanL | Mean | Cell of matrices | ||
LNormal_param/varianceL | Standard deviation (>0) | Cell of matrices | ||
Beta_param | Beta distribution parameters | Beta probability distribution parameters. | Structure | |
Beta_param/alpha | First shape (Alpha) (>0) | Cell of matrices | ||
Beta_param/beta | Second shape (Beta) (>0) | Cell of matrices | ||
Gamma_param | Gamma distribution parameters | Gamma probability distribution parameters. | Structure | |
Gamma_param/k | Shape (K) (>0) | Cell of matrices | ||
Gamma_param/theta | Scale (Theta) (>0) | Cell of matrices | ||
Chi_param | Chi-squared distribution parameters | Chi-squared probability distribution parameters. | Structure | |
Chi_param/K | Degree of freedom | Cell of matrices | ||
Exp_param | Exponential distribution parameters | Exponential probability distribution parameters. | Structure | |
Exp_param/lambda | Lambda (rate) (>0) | Cell of matrices | ||
F_param | F-distribution parameters | F probability distribution parameters. | Structure | |
F_param/d1 | Degrees of freedom 1 (>0) | Cell of matrices | ||
F_param/d2 | Degrees of freedom 2 (>0) | Cell of matrices | ||
T_param | T-distribution parameters | T probability distribution parameters. | Structure | |
T_param/t | Degree of freedom (>0) | Cell of matrices | ||
Pearson_param | Pearson distribution parameters | Pearson probability distribution parameters. | Structure | |
Pearson_param/mean | Mean | Cell of matrices | ||
Pearson_param/variance | Variance (>0) | Cell of matrices | ||
Pearson_param/skewness | Skewness | Cell of matrices | ||
Pearson_param/kurtosis | Kurtosis | Cell of matrices | ||
Inv_gamma_param | Inverse-Gamma distribution parameters | Inverse-Gamma probability distribution parameters. | Structure | |
Inv_gamma_param/alpha | Shape (Alpha) (>0) | Cell of matrices | ||
Inv_gamma_param/beta | Scale (Beta) (>0) | Cell of matrices | ||
Inv_beta_param | Inverse-Beta distribution parameters | Inverse-Beta probability distribution parameters. | Structure | |
Inv_beta_param/alpha | First shape (Alpha) (>0) | Cell of matrices | ||
Inv_beta_param/beta | Second shape (Beta) (>0) | Cell of matrices |
Ports
| Name | Type | Description | IO Type | Number |
|---|---|---|---|---|
Port 1 | explicit | output | 1 | |
Port 2 | activation | input | 1 |
Advanced Properties
| Name | Value | Description |
|---|---|---|
always active | no | Time Dependency = standard mode activated |
direct-feedthrough | no | |
zero-crossing | no | |
mode | no | |
continuous-time state | no | |
discrete-time state | yes |