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# Why Data Conversion?

Why Data Conversion?. Real world is analog Mostly, communication and computation is digital Need a component to convert analog signals to digital (ADC) and convert the processed digital signal back to analog (DAC). Types of Data Converters. Niquist rate data converters Serial

## Why Data Conversion?

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### Presentation Transcript

1. Why Data Conversion? • Real world is analog • Mostly, communication and computation is digital • Need a component to convert analog signals to digital (ADC) and convert the processed digital signal back to analog (DAC)

2. Types of Data Converters • Niquist rate data converters • Serial • Successive approximation • Flash • Oversampling (Sigma-Delta) How is a data converter characterized ??? • Power consumption • Area consumption • Operating speed • Conversion time (delay) • Error (Linearity) • Noise performance • And many more….

3. Integral Non-Linearity Error INL: Deviation of the code transition from its ideal location

4. Differential Non-Linearity Error DNL: Deviation of the code width from 1 LSB

5. Full Scale Error Full scale error: Difference between the actual value that triggers the transition to full-scale and the ideal analog full-scale transition value

6. Gain Error Gain error: Difference between the slope of an actual transfer function matches the slope of the ideal transfer function

7. Noise Performance SNR (signal to noise ratio): Ratio of the fundamental signal to the noise spectrum. THD (total harmonic distortion): Ratio of the fundamental signal to the noise spectrum. SFDR (spurious free dynamic range): Ratio of the fundamental signal and the highest spurious in the spectrum SINAD (Signal-to-Noise And Distortion): combination of SNR and THD SINAD = 20 * log ([Fundamental] / SQRT (SUM (SQR([Noise + Harmonics])))) ENOB (Effective Number of Bits): (SINAD – 1.76) / 6.02