Documentation 
Generate histogram of input or sequence of inputs
The Histogram block computes the frequency distribution of the elements in the input. You must use the Find the histogram over parameter to specify whether the block computes the histogram for Each column of the input or of the Entire input. The Running histogram check box allows you to select between basic operation and running operation, as described below.
The block distributes the elements of the input into the number of discrete bins specified by the Number of bins parameter, n.
y = hist(u,n) % Equivalent MATLAB code
The Histogram block sorts all complex input values into bins according to their magnitude.
The histogram value for a given bin represents the frequency of occurrence of the input values bracketed by that bin. You specify the upper boundary of the highestvalued bin in the Upper limit of histogram parameter, B_{M}, and the lower boundary of the lowestvalued bin in the Lower limit of histogram parameter, B_{m}. The bins have equal width of
$$\Delta =\frac{{B}_{M}{B}_{m}}{n}$$
and centers located at
$${B}_{m}+\left(k+\frac{1}{2}\right)\Delta \begin{array}{cccc}& & & k=0,1,2,\mathrm{...},n1\end{array}$$
Input values that fall on the border between two bins are placed into the lower valued bin; that is, each bin includes its upper boundary. For example, a bin of width 4 centered on the value 5 contains the input value 7, but not the input value 3. Input values greater than the Upper limit of histogram parameter or less than Lower limit of histogram parameter are placed into the highest valued or lowest valued bin, respectively.
The values you enter for the Upper limit of histogram and Lower limit of histogram parameters must be realvalued scalars. NaN and inf are not valid values for the Upper limit of histogram and Lower limit of histogram parameters.
When the Running histogram check box is not selected, the Histogram block computes the frequency distribution of the current input.
When you set the Find the histogram over parameter to Each column, the Histogram block computes a histogram for each column of the MbyN matrix independently. The block outputs an nbyN matrix, where n is the Number of bins you specify. The jth column of the output matrix contains the histogram for the data in the jth column of the MbyN input matrix.
When you set the Find the histogram over parameter to Entire input, the Histogram block computes the frequency distribution for the entire input vector, matrix or ND array. The block outputs an nby1 vector, where n is the Number of bins you specify.
When you select the Running histogram check box, the Histogram block computes the frequency distribution of both the past and present data for successive inputs. The block resets the histogram (by emptying all of the bins) when it detects a reset event at the optional Rst port. See Resetting the Running Histogram for more information on how to trigger a reset.
When you set the Find the histogram over parameter to Each column, the Histogram block computes a running histogram for each column of the MbyN matrix. The block outputs an nbyN matrix, where n is the Number of bins you specify. The jth column of the output matrix contains the running histogram for the jth column of the MbyN input matrix.
When you set the Find the histogram over parameter to Entire input, the Histogram block computes a running histogram for the data in the first dimension of the input. The block outputs an nby1 vector, where n is the Number of bins you specify.
Note: When the Histogram block is used in running mode and the input data type is nonfloating point, the output of the histogram is stored as a uint32 data type. The largest number that can be represented by this data type is 2^{32}1. If the range of the uint32 data type is exceeded, the output data will wrap back to 0. 
The block resets the running histogram whenever a reset event is detected at the optional Rst port. The reset signal and the input data signal must be the same rate.
You specify the reset event using the Reset port menu:
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)
Nonzero sample — Triggers a reset operation at each sample time that the Rst input is not zero
The bin boundaries created by the Histogram block are determined by the data type of the input:
Bin boundaries for real, doubleprecision input are cast into the data type double.
Bin boundaries for real, fixedpoint input are cast into the int8 data type.
The following example shows the differences in the output of the Histogram block based on the data type of the input.
To create this model you need the following blocks.
Block  Library  Quantity 

Constant  Simulink^{®} /Sources library  2 
Display  Sinks  2 
Histogram  Statistics  2 
The parameter settings for the Double Precision Input Constant block are:
Constant value = double([1 2 3 4 5]')
Interpret vector parameters as 1D = Clear this check box.
Sampling mode = Sample based
Sample time = inf
The parameter settings for the FixedPoint Input Constant block are:
Constant value = int8([1 2 3 4 5]')
Interpret vector parameters as 1D = Clear this check box.
Sampling mode = Sample based
Sample time = inf
The parameter settings for both Histogram blocks are:
Lower limit of histogram = 1
Upper limit of histogram = 3
Number of bins = 5
Find the histogram over = Entire input
Normalized = Clear this check box.
Running histogram = Clear this check box.
Connect the blocks as shown in the following figure, and run your model.
Running the fixedpoint model generates the following warning:
Warning: The bin width resulting from the specified parameters is less than the precision of the input data type. This might cause unexpected results. Since bin width is calculated by ((upper limit  lower limit)/number of bins), you could increase upper limit or decrease lower limit or number of bins.
This warning alerts you that it is not a good use case to have a histogram where 2 or more bin boundaries are the same. As the warning suggests, increasing the range of the limits of the histogram, or decreasing the number of bins, can correct this problem.
The Main pane of the Histogram block dialog appears as follows.
Enter a realvalued scalar for the lower boundary, B_{m}, of the lowestvalued bin. NaN and inf are not valid values for B_{m}. Tunable.
Enter a realvalued scalar for the upper boundary, B_{M}, of the highestvalued bin. NaN and inf are not valid values for B_{M}. Tunable.
The number of bins, n, in the histogram.
Specify whether the block finds the histogram over the entire input or along each column of the input.
When selected, the output vector, v, is normalized such that sum(v) = 1.
Use of this parameter is not supported for fixedpoint signals.
Set to enable the running histogram operation, and clear to enable basic histogram operation. For more information, see Basic Operation and Running Operation.
The type of event that resets the running histogram. For more information, see Resetting the Running Histogram. The reset signal and the input data signal must be the same rate. This parameter is enabled only when you select the Running histogram check box. For more information, see Running Operation.
The Data Types pane of the Histogram block dialog appears as follows.
Note: The fixedpoint parameters listed are only used for fixedpoint complex inputs, which are distributed by squared magnitude. 
Select the rounding mode for fixedpoint operations.
Select the overflow mode for fixedpoint operations.
Specify the product output data type. See Multiplication Data Types for illustrations depicting the use of the product output data type. You can set it to:
A rule that inherits a data type, for example, Inherit: Inherit via internal rule
An expression that evaluates to a valid data type, for example, fixdt([],16,0)
Click the Show data type assistant button to display the Data Type Assistant, which helps you set the Product output data type parameter.
See Specify Data Types Using Data Type Assistant for more information.
Specify the accumulator data type. You can set this parameter to:
A rule that inherits a data type, for example, Inherit: Inherit via internal rule
An expression that evaluates to a valid data type, for example, fixdt([],16,0)
Click the Show data type assistant button to display the Data Type Assistant, which helps you set the Accumulator data type parameter.
See Specify Data Types Using Data Type Assistant for more information.
Select this parameter to prevent the fixedpoint tools from overriding the data types you specify on the block mask.
Port  Supported Data Types 

In 

Output 

Rst 
