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Standard Deviation

Find standard deviation of input or sequence of inputs

Statistics

dspstat3

Description

The Standard Deviation block computes the standard deviation of each row or column of the input, along vectors of a specified dimension of the input, or of the entire input. The Standard Deviation block can also track the standard deviation of a sequence of inputs over a period of time. The Running standard deviation parameter selects between basic operation and running operation.

Basic Operation

When you do not select the Running standard deviation check box, the block computes the standard deviation of each row or column of the input, along vectors of a specified dimension of the input, or of the entire input at each individual sample time, and outputs the array y. Each element in y contains the standard deviation of the corresponding column, row, vector, or entire input. The output y depends on the setting of the Find the standard deviation value over parameter. For example, consider a 3-dimensional input signal of size M-by-N-by-P:

• Entire input — The output at each sample time is a scalar that contains the standard deviation of the entire input.

```y = std(u(:))					% Equivalent MATLAB code
```
• Each Row — The output at each sample time consists of an M-by-1-by-P array, where each element contains the standard deviation of each vector over the second dimension of the input. For an input that is an M-by-N matrix, the output at each sample time is an M-by-1 column vector.

```y = std(u,0,2)					% Equivalent MATLAB code
```
• Each Column — The output at each sample time consists of a 1-by-N-by-P array, where each element contains the standard deviation of each vector over the first dimension of the input. For an input that is an M-by-N matrix, the output at each sample time is a 1-by-N row vector.

```y = std(u,0,1)					% Equivalent MATLAB code
```

In this mode, the block treats length-M unoriented vector inputs as M-by-1 column vectors.

• Specified Dimension — The output at each sample time depends on Dimension. If Dimension is set to 1, the output is the same as when you select Each column. If Dimension is set to 2, the output is the same as when you select Each row. If Dimension is set to 3, the output at each sample time is an M-by-N matrix containing the standard deviation of each vector over the third dimension of the input.

```y = std(u,0,Dimension)					% Equivalent MATLAB code
```

For purely real or purely imaginary inputs, the standard deviation of the jth column of an M-by-N input matrix is the square root of its variance:

For complex inputs, the output is the total standard deviation, which equals the square root of the total variance, or the square root of the sum of the variances of the real and imaginary parts. The standard deviation of each column in an M-by-N input matrix is given by:

${\sigma }_{j}=\sqrt{{\sigma }_{j,\mathrm{Re}}^{2}+{\sigma }_{j,\mathrm{Im}}^{2}}$

 Note:   The total standard deviation does not equal the sum of the real and imaginary standard deviations.

Running Operation

When you select the Running standard deviation check box, the block tracks the standard deviation of successive inputs to the block. In this mode, you must also specify a value for the Input processing parameter:

• When you select Elements as channels (sample based), the block outputs an M-by-N array. Each element yij of the output contains the standard deviation of the element uij over all inputs since the last reset.

• When you select Columns as channels (frame based), the block outputs an M-by-N matrix. Each element yij of the output contains the standard deviation of the jth column over all inputs since the last reset, up to and including element uij of the current input.

Running Operation for Variable-Size Inputs

When your inputs are of variable size, and you select the Running standard deviation check box, there are two options:

• If you set the Input processing parameter to Elements as channels (sample based), the state is reset.

• If you set the Input processing parameter to Columns as channels (frame based), then there are two cases:

• When the input size difference is in the number of channels (i.e., number of columns), the state is reset.

• When the input size difference is in the length of channels (i.e., number of rows), there is no reset and the running operation is carried out as usual.

Resetting the Running Standard Deviation

The block resets the running standard deviation whenever a reset event is detected at the optional Rst port. The reset sample time must be a positive integer multiple of the input sample time.

You specify the reset event in the Reset port parameter:

• None disables the Rst port.

• Rising edge — Triggers a reset operation when the Rst input does one of the following:

• Rises from a negative value to a positive value or zero

• Rises from zero to a positive value, where the rise is not a continuation of a rise from a negative value to zero (see the following figure)

• Falling edge — Triggers a reset operation when the Rst input does one of the following:

• Falls from a positive value to a negative value or zero

• Falls from zero to a negative value, where the fall is not a continuation of a fall from a positive value to zero (see the following figure)

• Either edge — Triggers a reset operation when the Rst input is a Rising edge or Falling edge (as described earlier)

• Non-zero sample — Triggers a reset operation at each sample time that the Rst input is not zero

 Note:   When running simulations in the Simulink® MultiTasking mode, reset signals have a one-sample latency. Therefore, when the block detects a reset event, there is a one-sample delay at the reset port rate before the block applies the reset. For more information on latency and the Simulink tasking modes, see Excess Algorithmic Delay (Tasking Latency) and Scheduling in the Simulink Coder™ User's Guide.

ROI Processing

To calculate the statistical value within a particular region of interest (ROI) of the input, select the Enable ROI processing check box. This option is only available when the Find the standard deviation value over parameter is set to Entire input and the Running standard deviation check box is not selected. ROI processing is only supported for 2-D inputs.

 Note:   Full ROI processing is available only if you have a Computer Vision System Toolbox™ license. If you do not have a Computer Vision System Toolbox license, you can still use ROI processing, but are limited to the ROI type Rectangles.

Use the ROI type parameter to specify whether the ROI is a rectangle, line, label matrix, or binary mask. A binary mask is a binary image that enables you to specify which pixels to highlight, or select. In a label matrix, pixels equal to 0 represent the background, pixels equal to 1 represent the first object, pixels equal to 2 represent the second object, and so on. When the ROI type parameter is set to Label matrix, the Label and Label Numbers ports appear on the block. Use the Label Numbers port to specify the objects in the label matrix for which the block calculates statistics. The input to this port must be a vector of scalar values that correspond to the labeled regions in the label matrix. For more information about the format of the input to the ROI port when the ROI is a rectangle or a line, see the Draw Shapes block reference page.

For rectangular ROIs, use the ROI portion to process parameter to specify whether to calculate the statistical value for the entire ROI or just the ROI perimeter.

Use the Output parameter to specify the block output. The block can output separate statistical values for each ROI or the statistical value for all specified ROIs. This parameter is not available if, for the ROI type parameter, you select Binary mask.

If, for the ROI type parameter, you select Rectangles or Lines, the Output flag indicating if ROI is within image bounds check box appears in the dialog box. If you select this check box, the Flag port appears on the block. The following tables describe the Flag port output based on the block parameters.

Output = Individual statistics for each ROI

Flag Port OutputDescription
0ROI is completely outside the input image.
1ROI is completely or partially inside the input image.

Output = Single statistic for all ROIs

Flag Port OutputDescription
0All ROIs are completely outside the input image.
1At least one ROI is completely or partially inside the input image.

If the ROI is partially outside the image, the block only computes the statistical values for the portion of the ROI that is within the image.

If, for the ROI type parameter, you select Label matrix, the Output flag indicating if input label numbers are valid check box appears in the dialog box. If you select this check box, the Flag port appears on the block. The following tables describe the Flag port output based on the block parameters.

Output = Individual statistics for each ROI

Flag Port OutputDescription
0Label number is not in the label matrix.
1Label number is in the label matrix.

Output = Single statistic for all ROIs

Flag Port OutputDescription
0None of the label numbers are in the label matrix.
1At least one of the label numbers is in the label matrix.

Examples

In the following ex_standarddeviation_refex_standarddeviation_ref model, the Standard Deviation block calculates the running standard deviation of a 3-by-2 matrix input, u. The Input processing parameter is set to Columns as channels (frame based), so the block processes the input as a two channel signal with a frame size of three. The running standard deviation is reset at t=2 by an impulse to the block's Rst port.

The operation of the block is shown in the following figure.

Dialog Box

Running standard deviation

Enables running operation when selected.

Input processing

Specify how the block should process the input when computing the running standard deviation. You can set this parameter to one of the following options:

• Columns as channels (frame based) — When you select this option, the block treats each column of the input as a separate channel.

• Elements as channels (sample based) — When you select this option, the block treats each element of the input as a separate channel.

This parameter appears only when you select the Running standard deviation check box.

 Note:   The option Inherit from input (this choice will be removed - see release notes) will be removed in a future release. See Frame-Based Processing in the DSP System Toolbox™ Release Notes for more information.
Reset port

Specify the reset event that causes the block to reset the running standard deviation. The sample time of the input to the Rst port must be a positive integer multiple of the input sample time. This parameter appears only when you select the Running standard deviation check box. For more information, see Resetting the Running Standard Deviation.

Find the standard deviation value over

Specify whether to find the standard deviation value along rows, columns, entire input, or the dimension specified in the Dimension parameter. For more information, see Basic Operation.

Treat sample-based row input as a column

Select to treat sample-based length-M row vector inputs as M-by-1 column vectors. This parameter is only visible when the Find the standard deviation value over parameter is set to Each column.

 Note:   This check box will be removed in a future release. See Sample-Based Row Vector Processing Changes for more information.
Dimension

Specify the dimension (one-based value) of the input signal, over which the standard deviation is computed. The value of this parameter cannot exceed the number of dimensions in the input signal. This parameter is only visible when the Find the standard deviation value over parameter is set to Specified dimension.

Enable ROI Processing

Select this check box to calculate the statistical value within a particular region of each image. This parameter is only available when the Find the standard deviation value over parameter is set to Entire input, and the block is not in running mode.

 Note   Full ROI processing is available only when you have a Computer Vision System Toolbox license. If you do not have a Computer Vision System Toolbox license, you can still use ROI processing, but are limited to the ROI type Rectangles.
ROI type

Specify the type of ROI you want to use. Your choices are Rectangles, Lines, Label matrix, or Binary mask.

ROI portion to process

Specify whether you want to calculate the statistical value for the entire ROI or just the ROI perimeter. This parameter is only visible if, for the ROI type parameter, you specify Rectangles.

Output

Specify the block output. The block can output a vector of separate statistical values for each ROI or a scalar value that represents the statistical value for all the specified ROIs. This parameter is not available if, for the ROI type parameter, you select Binary mask.

Output flag

Output flag indicating if ROI is within image bounds

Output flag indicating if label numbers are valid

When you select either of these check boxes, the Flag port appears on the block. For a description of the Flag port output, see the tables in ROI Processing.

The Output flag indicating if ROI is within image bounds check box is only visible when you select Rectangles or Lines as the ROI type.

The Output flag indicating if label numbers are valid check box is only visible when you select Label matrix for the ROI type parameter.

Supported Data Types

PortSupported Data Types

Input

• Double-precision floating point

• Single-precision floating point

Reset

• Double-precision floating point

• Single-precision floating point

• Boolean

• 8-, 16-, and 32-bit signed integers

• 8-, 16-, and 32-bit unsigned integers

ROI

Rectangles and lines:

• Double-precision floating point

• Single-precision floating point

• Boolean

• 8-, 16-, and 32-bit signed integers

• 8-, 16-, and 32-bit unsigned integers

• Boolean

Label

• 8-, 16-, and 32-bit unsigned integers

Label Numbers

• 8-, 16-, and 32-bit unsigned integers

Output

• Double-precision floating point

• Single-precision floating point

Flag

• Boolean