The model is used to average a series of real-valued numbers. Each

cause the mean value of all numbers placed on the

signal to be placed on the

Input Ports

in Data Type: REALclr Data Type: TRIGGERtest Data Type: TRIGGER

Output Ports

avg Data Type: REAL

- none

The model extracts the largest real value from a series of real input values.

When the

input is placed on the

value is reset to a very small value.

Input Ports

input Data Type: REALtest Data Type: TRIGGER

Output Ports

maximum Data Type: REAL

- none

The model takes a series of REAL value inputs and averages all values which

come in over a batch period. At the end of the batch period, the average will be

written to the output and then the average will be cleared. Inputs are grouped

according to time batches. The duration of each batch is determined by two parameters:

Input Ports

in Data Type: REAL

Output Ports

avg Data Type: REAL

*NBatches Data Type: INTEGER**StartTime Data Type: REAL*

The model extracts the smallest real value from a series of real input values.

When the

input is placed on the

value is reset to a very large value.

Input Ports

input Data Type: REALtest Data Type: TRIGGER

Output Ports

minimum Data Type: REAL

- none

The model will output the basic statistics computed from input numbers

separated into different (time) batches. The batches are fixed length in time

and are of equal duration. All inputs which occur before the simulation clock

reaches the value of the

the remaining simulation time is divided into equal length batches and the basic

statistics for all values which come in during a batch period are placed on the

output port at the end of each batch period.

The simulation time is divided into equal time intervals according to two parameters:

Input Ports

input Data Type: REAL

Output Ports

stats Data Type: Complex Structure "Basic_statistic"

*NBatches Data Type: INTEGER**StartTime = 0.0 Data Type: REAL**NoSampleMean*= 0.0*NoSampleVariance*= -1.0

The model generates trigger signals to be used for batch statistic compilation.

The

when Tnow = (

Batch Period = (TSTOP -

Input Ports

none

Output Ports

Startup< Data Type: TRIGGERBatch< Data Type: TRIGGER

*NBatches Data Type: INTEGER**StartTime Data Type: REAL*

The model creates a Dimensioned Stats data structure and inserts the Mean,

Nsamps, and Dimension fields from the values of the inputs.

Input Ports

Mean Data Type: REAL

Nsamps Data Type: INTEGERDimension Data Type: INTEGER

Output Ports

out Data Type: Dimensioned Stats

*none*

The model creates a time average Statistics data structure and inserts the Mean,

Duration, and Dimension fields from the values of the inputs.

Input Port

Mean Data Type: REAL

Duration Data Type: REALDimension Data Type: INTEGER

Output Ports

out Data Type: time average stats

*none*

The model computes an ensemble average for each of several dimensions.

An ensemble average is the sum of all the

divided by the number of inputs in the sum. The number of dimensions must be

set with

To access the time average, enable the

For that dimension, the average will be computed and placed on the

number of samples in the average is placed on the

To reset dimensions enable the

history for the dimension will be cleared.

Input Ports

value Data Type: REALdim Data Type: INTEGERreset_dim Data Type: INTEGERtest_dim Data Type: INTEGERmax_dim Data Type: INTEGER

Output Ports

avg Data Type: REALcount Data Type: INTEGER

*Max_Dimensions*= 10*Data Type: INTEGER*

The model computes an time average for each of several dimensions.

A time average is the area under a plot of a value versus time divided by the

length of time of the observation.

To access the time average, enable the

dimension. For that dimension, the time average will be computed and placed

on the

calculated is placed on the

To reset the time average enable the

and all previous history for the dimension will be cleared.

Input Ports

value Data Type: REAL

dim Data Type: INTEGERreset_dim Data Type: INTEGERtest_dim Data Type: INTEGERmax_dim Data Type: INTEGER

Output Ports

avg Data Type: REALduration Data Type: REAL

*Max_Dimensions*= 10*Data Type: INTEGER*

The model takes the value which is to be added to the histogram

and computes the bin number into which the value should be placed.

The model outputs the bin number.

Input Ports

in Data Type: REAL

Output Ports

bin Data Type: INTEGER

*NBins Data Type: INTEGER**UpperBoundary Data Type: REAL**LowerBoundary Data Type: REAL*

The model computes the N-th moment of a set of real-valued inputs,

where N is a parameter of the model.

The model adds and removes numbers fron the data set. Numbers to

be added to the set should enter the module on the

numbers to be removed should be enter on the

can also be cleared by triggering the

Triggering the

in the data set onto

moment onto the

Input Ports

add Data Type: REAL

remove Data Type: REALreset Data Type: TRIGGERtest Data Type: TRIGGER

Output Ports

moment_out Data Type: REALnum_samples Data Type: INTEGER

*Moment Data Type: INTEGER**ZeroSampOut*=0.0*Data Type: REAL*

after the last enabling of the

The three parameters of the model specify the number of bins (intervals)

and the range of values which be used to create the histogram.

Input Ports

in Data Type: REALclr Data Type: TRIGGERtest Data Type: TRIGGER

Output Ports

histo Data Type: Histogram Report DS

*NBins Data Type: INTEGER**UpperBoundary Data Type: REAL**LowerBoundary Data Type: REAL*

The model computes the mean and variance from a series of real-vaued inputs. The sample variance is

computed as {((n/(n-1)) * [(the 2nd moment of the input values) minus (the square of the sample mean)]}

where

If the number of samples is zero, the value of

number of samples is zero or one, the value of

The reset input provides the ability to clear out the entire data set

Input Ports

add Data Type: REALremove Data Type: REALreset Data Type: TRIGGERtest Data Type: TRIGGER

Output Ports

mean Data Type: REALvariance Data Type: REALnum_samples Data Type: INTEGER

*ZeroSampMean = 0.0 Data Type: REAL**ZeroSampVar = 0.0 Data Type: REAL*

the ratio of the average rate of information bits flowing through the link to the capacity of the link.

The models input should be connected to the number of information bits in the packets as the flow

through a link. The model will compute a time varing throughput according to the following three

parameters.

Input Ports

in Data Type: REAL

Output Ports

out Data Type: REAL

*Capacity Data Type: REAL**OutputPeriod Data Type: REAL**WindowPeriod Data Type: REAL*

The model will take a series of real-valued inputs and find their time average. Each input will be

weighted by the difference in time from when it comes in to the time the next input comes in.

The value of

of each simulation.

Input Ports

input Data Type: REALreset Data Type: TRIGGERtest Data Type: TRIGGER

Output Ports

avg Data Type: REAL

*none*

The model computes the Weighted N-th moment of a set or real-valued inputs. N is a parameter of the

model.

The model is useful for computing the means and variance from a set of sampled data. The weight input

corresponds to the number of samples from the orginal data that were used to calculate each input to the

model.

Triggering the

output port and the computed moment onto the

samples is placed on the

If the sum of the weights given is zero then the value of the parameter

Input Ports

samp_in Data Type: REALweight Data Type: REALreset Data Type: TRIGGERtest Data Type: TRIGGER

Output Ports

moment_out Data Type: REALnum_samples Data Type: INTEGERtotal_weights Data Type: REAL

*Moment Data Type: INTEGER**ZeroSampOut = 0.0 Data Type: REAL*

The model computes the mean and variance from a series of real-vaued inputs. The sample variance is

computed as {((n/(n-1)) * [(the 2nd moment of the input values) minus (the square of the sample mean)]}

where

If the number of samples is zero, the value of

number of samples is zero or one, the value of

The reset input provides the ability to clear out the entire data set.

Input Ports

samp_in Data Type: REALweight Data Type: REALreset Data Type: TRIGGERtest Data Type: TRIGGER

Output Ports

mean Data Type: REALvariance Data Type: REALnum_samples Data Type: INTEGER

*ZeroSampMean = 0.0 Data Type: REAL**ZeroSampVar= 0.0 Data Type: REAL*

The model will output the basic statistics computed from

input numbers separated into different (time) batches.

The batches are fixed length in time and are of equal

duration. All inputs which occur before the simulation

clock reaches the value of the StartTime parameter are

discarded. After the start time, the remaining simulation

time is divided into equal length batches and the basic

statistics for all values which come in during a batch

period are placed on the stats output port at the end of

each batch period. The simulation time is divided into

equal time intervals according to two parameters:

NBatches and StartTime.

Input Ports

input Data Type: REAL

Output Ports

stats Data Type: Complex Structure "Basic_statistic"

Parameters

NBatches Data Type: INTEGEREndTime = 100.0 Data Type: REAL

NoSampleMean = 0.0 Data Type: REAL

NoSampleVariance = -1.0 Data Type: REAL