Random Source (DSP Blockset)

Generate randomly distributed values.

Library

Description

The Random Source block generates a frame of M values drawn from a uniform or Gaussian pseudorandom distribution, where M is specified by the Samples per frame parameter.

This reference page contains a detailed discussion of the following Random Source block topics:

Distribution Type

When the Source type parameter is set to Uniform, the output samples are drawn from a uniform distribution whose minimum and maximum values are specified by the Minimum and Maximum parameters, respectively. All values in this range are equally likely to be selected. A length-N vector specified for one or both of these parameters generates an N-channel output (M-by-N matrix) containing a unique random distribution in each channel.

For example, specify

Minimum = [ 0 0 -3 -3]
Maximum = [10 10 20 20]

to generate a four-channel output whose first and second columns contain random values in the range [0, 10], and whose third and fourth columns contain random values in the range [-3, 20]. When only one of the Minimum and Maximum parameters is specified as a vector, the other is scalar expanded to the same length.

When the Source type parameter is set to Gaussian, you must also set the Method parameter, which determines the method by which the block computes the output and has the following settings:

Ziggurat -- The block produces Gaussian random values by using the Ziggurat method, which is the same method used by the MATLAB randn function.
Sum of uniform values -- The block produces Gaussian random values by adding and scaling uniformly distributed random signals. You must set the Number of uniform values to sum parameter, which determines the number of uniformly distributed random numbers to sum to produce a single Gaussian random value.

For both settings of the Method parameter, the output samples are drawn from the normal distribution defined by the Mean and Variance parameters. A length-N vector specified for one or both of the Mean and Variance parameters generates an N-channel output (M-by-N frame matrix) containing a distinct random distribution in each column. When only one of these parameters is specified as a vector, the other is scalar expanded to the same length.

Output Complexity

The block's output can be either real or complex, as selected by the Real and Complex options in the Output complexity parameter. (These settings control all channels of the output, so real and complex data cannot be combined in the same output.) For complex output with a Uniform distribution, the real and imaginary components in each channel are both drawn from the same uniform random distribution, defined by the Minimum and Maximum parameters for that channel.

For complex output with a Gaussian distribution, the real and imaginary components in each channel are drawn from normal distributions with different means. In this case, the Mean parameter for each channel should specify a complex value; the real component of the Mean parameter specifies the mean of the real components in the channel, while the imaginary component specifies the mean of the imaginary components in the channel. If either the real or imaginary component is omitted from the Mean parameter, a default value of 0 is used for the mean of that component.

For example, a Mean parameter setting of [5+2i 0.5 3i] generates a three-channel output with the following means.

Channel 1 mean
real = 5
imaginary = 2

Channel 2 mean
real = 0.5
imaginary = 0

Channel 3 mean
real = 0
imaginary = 3

Channel 1 mean	real = 5	imaginary = 2
Channel 2 mean	real = 0.5	imaginary = 0
Channel 3 mean	real = 0	imaginary = 3

For complex output, the Variance parameter, ², specifies the total variance for each output channel. This is the sum of the variances of the real and imaginary components in that channel.

The specified variance is equally divided between the real and imaginary components, so that

Output Repeatability

The Repeatability parameter determines whether or not the block outputs the same signal each time you run the simulation. You can set the parameter to one of the following options:

Repeatable -- The block outputs the same signal each time you run the simulation. The first time you run the simulation, the block randomly selects an initial seed. The block reuses these same initial seeds every time you rerun the simulation.
Specify seed -- The block outputs the same signal each time you run the simulation. Every time you run the simulation, the block uses the initial seed(s) specified in the Initial seed parameter. Also see the next section, Specifying the Initial Seed.
Not repeatable -- The block does not output the same signal each time you run the simulation. Every time you run the simulation, the block randomly selects an initial seed.

Specifying the Initial Seed

When you set the Repeatability parameter to Specify seed, you must set the Initial seed parameter. The Initial seed parameter specifies the initial seed for the pseudorandom number generator. The generator produces an identical sequence of pseudorandom numbers each time it is executed with a particular initial seed.

Specifying Initial Seeds for Real Outputs. To specify the N initial seeds for an N-channel real-valued output (Output complexity parameter set to Real), provide one of the following in the Initial seed parameter:

Length-N vector of initial seeds -- The block uses each vector element as an initial seed for the corresponding channel in the N-channel output.
Single scalar -- The block uses the scalar to generate N random values, which it uses as the seeds for the N-channel output.

Specifying Initial Seeds for Complex Outputs. To specify the initial seeds for an N-channel complex-valued output (Output complexity parameter set to Complex), provide one of the following in the Initial seed parameter:

Length-N vector of initial seeds -- The block uses each vector element as an initial seed for generating N channels of real random values. The block uses pairs of adjacent values in each of these channels as the real and imaginary components of the final output, as illustrated in the following figure.
Single scalar -- The block uses the scalar to generate N random values, which it uses as the seeds for generating N channels of real random values. The block uses pairs of adjacent values in each of these channels as the real and imaginary components of the final output, as illustrated in the following figure.

Sample Period

The Sample time parameter value, T_s, specifies the random sequence sample period when the Sample mode parameter is set to Discrete. In this mode, the block generates the number of samples specified by the Samples per frame parameter value, M, and outputs this frame with a period of M*T_s. For M=1, the output is sample-based; otherwise, the output is frame-based.

When Sample mode is set to Continuous, the block is configured for continuous-time operation, and the Sample time and Samples per frame parameters are disabled. Note that many blocks in the DSP Blockset do not accept continuous-time inputs.

Dialog Box

Only some of the parameters described below are visible in the dialog box at any one time.

Source type: The distribution from which to draw the random values, Uniform or Gaussian. For more information, see Distribution Type.
Method: The method by which the block computes the Gaussian random values, Ziggurat or Sum of uniform values. This parameter is enabled when Source type is set to Gaussian. For more information, see Distribution Type.
Minimum: The minimum value in the uniform distribution. This parameter is enabled when Uniform is selected from the Source type parameter. Tunable.
Maximum: The maximum value in the uniform distribution. This parameter is enabled when Uniform is selected from the Source type parameter. Tunable.
Number of uniform values to sum: The number of uniformly distributed random values to sum to compute a single number in a Gaussian random distribution. This parameter is enabled when the Source type parameter is set to Gaussian, and the Method parameter is set to Sum of uniform values. For more information, see Distribution Type.
Mean: The mean of the Gaussian (normal) distribution. This parameter is enabled when Gaussian is selected from the Source type parameter. Tunable.
Variance: The variance of the Gaussian (normal) distribution. This parameter is enabled when Gaussian is selected from the Source type parameter. Tunable.
Repeatability: The repeatability of the block output: Not repeatable, Repeatable, or Specify seed. In the Repeatable and Specify seed settings, the block outputs the same signal every time you run the simulation. For details, see Output Repeatability.
Initial seed: The initial seed(s) to use for the random number generator when you set the Repeatability parameter to Specify seed. For details, see Specifying the Initial Seed.
Inherit output port attributes: When selected, allows the block to inherit the sample mode, sample period, and complexity of a downstream block. (The Sample mode, Sample time, Samples per frame, and Output complexity parameters are disabled.) The output is a length-M sample-based 1-D vector, where length M is inherited from the downstream block. If the Minimum, Maximum, Mean, or Variance parameter specifies N channels, the 1-D vector output contains M/N samples from each channel. An error occurs in this case if M is not an integer multiple of N.
Sample mode: The sample mode, Continuous or Discrete. This parameter is enabled when the Inherit output port attributes check box is cleared.
Sample time: The sample period, T_s, of the random output sequence. The output frame period is M*T_s. This parameter is enabled when the Inherit output port attributes check box is cleared.
Samples per frame: The number of samples, M, in each output frame. This parameter is enabled when the Inherit output port attributes check box is cleared.
Output data type: The data type of the output, single-precision or double-precision. This parameter is enabled when the Inherit output port attributes check box is cleared.
Output complexity: The complexity of the output, Real or Complex. This parameter is enabled when the Inherit output port attributes check box is cleared.

Supported Data Types

Double-precision floating point
Single-precision floating point

To learn how to convert to the above data types in MATLAB and Simulink, see Supported Data Types and How to Convert to Them.

See Also

Discrete Impulse
DSP Blockset

DSP Constant
DSP Blockset

Maximum
DSP Blockset

Minimum
DSP Blockset

Signal From Workspace
DSP Blockset

Standard Deviation
DSP Blockset

Variance
DSP Blockset

Random Number
Simulink

Signal Generator
Simulink

rand
MATLAB

randn
MATLAB

Discrete Impulse	DSP Blockset
DSP Constant	DSP Blockset
Maximum	DSP Blockset
Minimum	DSP Blockset
Signal From Workspace	DSP Blockset
Standard Deviation	DSP Blockset
Variance	DSP Blockset
Random Number	Simulink
Signal Generator	Simulink
`rand`	MATLAB
`randn`	MATLAB

Also see the following topics:

Creating Signals Using Signal Generator Blocks -- How to use this and other blocks to generate signals
DSP Sources -- List of all blocks in the DSP Sources library

Queue Real Cepstrum