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Current Steering Digital-to-Analog Converters
Published in Krzysztof Iniewski, Circuits at the Nanoscale, 2018
A number of factors affect static or DC performance. Gain error is the deviation of the slope of the converter’s transfer function from that of the ideal transfer function (see Figure 12.1). Offset error is the deviation of the DAC output from that of the ideal transfer function when gain error is zero. Offset error is thus constant for all input codes. Differential nonlinearity (DNL) is the deviation of the actual step size at each input code from the ideal 1-LSB step. DNL errors can result in additive noise and spurs beyond quantization effects. Integral nonlinearity (INL) is the deviation of the actual output voltage from the ideal output voltage on a straight line drawn between the end points of the transfer function. INL is calculated after offset and gain errors are removed. INL error can also result in additive harmonics and spurs in the output. A DAC is monotonic if its output increases or remains the same for an increment in the digital input code. Conversely, a DAC is nonmonotonic if the output decreases for an increment in the digital code.
Analog-to-Digital Conversion
Published in David R. Martinez, Robert A. Bond, Vai M. Michael, High Performance Embedded Computing Handbook, 2018
James C. Anderson, Helen H. Kim
For an ideal ADC, the difference in the analog input voltage is constant from one output code transition point to the next. The differential nonlinearity (DNL) for a nonideal ADC (after compensating for any offset and gain errors) specifies the deviation of any code in the transfer function from the ideal code width of one LSB. DNL test data for an ADC may be provided in the form of a graph that shows DNL values (relative to an LSB) versus the digital code. If specifications indicate a minimum value of −1 for DNL, then missing codes will occur; i.e., specific output codes will not reliably be produced by the ADC in response to any analog input voltage. Changes in DNL as a function of time create a dynamic DNL.
Image-Processing Engines
Published in Junichi Nakamura, Image Sensors and Signal Processing for Digital Still Cameras, 2017
Nonlinearity. In imaging applications, special care is needed to keep the signal monotonic over the dynamic range of the image data. Differential nonlinearity (DNL) is the indicator to evaluate the monotonicity of the conversion characteristic (±1/2 LSB is needed to guarantee no missing codes). Integral nonlinearity (INL) should also be addressed because the smoothness of an INL curve is quite important to obtain a good monotonic signal (±1 LSB is desirable to avoid affecting gamma compensation).
Time domain modelled ADC BIST with ramp noise projection
Published in International Journal of Electronics, 2019
M. Senthil Sivakumar, S. P. Joy Vasantha Rani
where Vamax and Vimax are the last reference voltages of the actual and ideal characteristics, respectively. Code width of the data converter is basically affected by nonlinearity errors. Differential nonlinearity (DNL) is measured as the difference between actual code width from ideal 1.LSB width.