DAC DC Measurement
Libraries:
Mixed-Signal Blockset /
DAC /
Measurements & Testbenches
Description
The DAC DC Measurement block measures DAC DC performance metrics such as offset error, gain error, integral nonlinearity (INL), and differential nonlinearity (DNL) errors. You can use the DAC DC Measurement block to validate the DAC architecture models provided in Mixed-Signal Blockset™, or you can use a DAC of your own implementation.
Examples
Ports
Input
digital — Digital input signal from DAC
scalar
Digital signal from a DAC, specified as a scalar.
Data Types: fixed point
| single
| double
| int8
| int16
| int32
| uint8
| uint16
| uint32
analog — Converted analog signal from DAC
scalar
Converted analog signal from a DAC, specified as a scalar.
Data Types: double
start — External clock to start conversion
scalar
External clock to start conversion, specified as a scalar. This port determines when digital-to-analog conversion process starts.
Data Types: double
Parameters
Input polarity — Polarity of input signal to DAC
Bipolar
(default) | Unipolar
Polarity of the input signal to the DAC.
Programmatic Use
Block parameter:
Polarity |
Type: character vector |
Values:
Bipolar |Unipolar |
Default:
Bipolar |
Reference (V) — Reference voltage
2
(default) | real scalar
Reference voltage of the DAC, specified as a real scalar in volts. Reference (V) helps determine the output from the input digital code, Number of bits, and Bias (V) using the equation:
.
Programmatic Use
Block parameter:
Ref |
Type: character vector |
Values: real scalar |
Default:
2 |
Data Types: double
Bias (V) — Bias voltage added to output
0
(default) | real scalar
Bias voltage added to the output of the DAC, specified as a real scalar in volts. Bias (V) helps determine the output from the input digital code, Number of bits, and Reference (V) using the equation:
.
Programmatic Use
Block parameter:
Bias |
Type: character vector |
Values: real scalar |
Default:
0 |
Data Types: double
Settling time (s) — Time required for output to settle
3e-7
(default) | nonnegative real scalar
The time required for the output of the DAC to settle to within some fraction of its final value, specified as a nonnegative real scalar in seconds.
Programmatic Use
Block parameter:
SettlingTime |
Type: character vector |
Values: real scalar |
Default:
3e-7 |
Data Types: double
Hold off time (s) — Delay before measurement analysis
1e-3
(default) | nonnegative real scalar
Delay before measurement analysis to avoid corruption by transients, specified as a nonnegative real scalar in seconds.
Programmatic Use
Block parameter:
HoldOffTime |
Type: character vector |
Values: nonnegative real scalar |
Default:
1e-3 |
Data Types: double
Number of bits — Number of bits in input word
10
(default) | positive real integer
Number of bits in the input word, specified as a unitless positive real integer. Number of bits determines the resolution of the DAC.
Programmatic Use
Block parameter:
NBits |
Type: character vector |
Values: positive real integer |
Default:
10 |
Data Types: double
Start conversion frequency (Hz) — Frequency of internal start conversion clock
1e6
(default) | positive real scalar
Frequency of the internal start conversion clock, specified as a real scalar in Hz. The Start conversion frequency parameter determines the conversion rate at the start of conversion.
Programmatic Use
Block parameter:
StartFreq |
Type: character vector |
Values: positive real scalar |
Default:
1e6 |
Data Types: double
Recommended simulation stop time (s) — Minimum time simulation must run for meaningful result
0.02148
(default) | positive real scalar
Minimum time the simulation must run to obtain meaningful results, specified as a positive real scalar in seconds.
To measure DC performance, the simulation must run so that the DAC can sample each digital code 20 times. Based on this assumption, the Recommended simulation stop time (s) T is given by:
,
where StartFreq is the frequency of the conversion start clock and Nbits is the resolution of the DAC.
The number of samples per bit is calculated using the equation:
.
This parameter is only reported by the block and is not editable.
Data Types: double
Endpoint — Measure DNL, INL using endpoint method
on (default) | off
Measure the differential nonlinearity (DNL) error and integral nonlinearity (INL) error using the endpoint method. This method uses the endpoints of the actual transfer function to measure the DNL and INL errors.
Best fit — Measure DNL, INL using best fit method
on (default) | off
Measure the differential nonlinearity (DNL) error and integral nonlinearity (INL) error using the best fit method. This method uses a standard curve-fitting technique to find the best fit to measure the DNL and INL errors.
Output result to base workspace — Store detailed test results to base workspace
off (default) | on
Select to store detailed test results to a struct
in the base
workspace for further processing at the end of simulation. By default, this parameter is
deselected.
Workspace variable name — Name of the variable that stores detailed test results
dac_dc_out
(default) | character string
Name of the variable that stores detailed test results, specified as a character string.
Dependencies
To enable this parameter, select Output result to base workspace parameter.
Programmatic Use
Block parameter:
VariableName |
Type: character vector |
Values: character string |
Default:
dac_dc_out |
Plot — Plot measurement results
button
Click to plot measurement result for further analysis.
More About
Offset Error
Offset error represents the offset of the DAC transfer function curve from it ideal value at a single point.
Gain Error
Gain error represents the deviation of the slope of the DAC transfer function curve from its ideal value.
INL Error
Integral nonlinearity (INL) error, also termed as relative accuracy, is the maximum deviation of the measured transfer function from a straight line. The straight line can either be a best fit using standard-curve fitting technique, or be drawn between the endpoints of the actual transfer function after gain adjustment.
The best fit method gives a better prediction of distortion in AC applications, and a lower value of linearity error. The endpoint method is mostly used in the measurement applications of data converters, since the error budget depends on actual deviation from the ideal transfer function.
DNL Error
Differential nonlinearity (DNL) is the deviation from the ideal difference (1 LSB) between analog input levels that trigger any two successive digital output levels. The DNL error is the maximum value of DNL found at any transition.
Version History
Introduced in R2020a
See Also
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