DSP Blockset

Random Source

Generate randomly distributed values

Library

DSP Sources

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
• Output Complexity
• Output Repeatability
• Specifying the Initial Seed
• Sample Period
• Dialog Box
• Supported Data Types
• See Also

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 block scalar expands the other parameter so it is the same length as the vector.

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 -- Produces Gaussian random values by using the Ziggurat method, which is the same method used by the MATLAB randn function.
• Sum of uniform values -- 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 block scalar expands the other parameter so it is the same length as the vector.

Output Complexity

The block's output can be either real or complex, as determined by the Real and Complex options in the 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

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 -- 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 -- 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 -- 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 (Complexity parameter set to Real), provide one of the following in the Initial seed parameter:

• Length-N vector of initial seeds -- Uses each vector element as an initial seed for the corresponding channel in the N-channel output.
• Single scalar -- 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 (Complexity parameter set to Complex), provide one of the following in the Initial seed parameter:

• Length-N vector of initial seeds -- 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 -- 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.

Opening this dialog box causes a running simulation to pause. See Changing Source Block Parameters in the online Simulink documentation for details.

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 you select this check box, block inherits the sample mode, sample time, output data type, complexity, and signal dimensions of a sample-based signal from a downstream block. When you select this check box, the Sample mode, Sample time, Samples per frame, Output data type, and Complexity parameters are disabled.

Suppose you want to back propagate a 1-D vector. The output of the Random Source block 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.

Suppose you want to back propagate a M-by-N signal. If N>1, your signal has N channels. If N = 1, your signal has M channels. The value of the Minimum, Maximum, Mean, or Variance parameter can be a scalar or a vector of length equal to the number of channels. You can specify these parameters as either row or column vectors, except when the signal is a row vector. In this case, the Minimum, Maximum, Mean, or Variance parameter must also be specified as a row vector.

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 your data types 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

Also see Creating Signals Using Signal Generator Blocks for how to use this and other blocks to generate signals.

Queue

Real Cepstrum