The Analogue-to-digital converter (ADC) is the most pervasive block in electronic systems. With the advent of powerful digital signal processing and digital communication techniques, ADCs are fast becoming critical components for systema (TM)s performance and flexibility. Knowing accurately all the parameters that characterise their dynamic behaviour is crucial, on one hand to select the most adequate ADC architecture and characteristics for each end application, and on the other hand, to understand how they affect performance bottlenecks in the signal processing chain.

Dynamic Characterisation of Analogue-to-Digital Converters presents a state of the art overview of the methods and procedures employed for characterising ADCsa (TM) dynamic performance behaviour using sinusoidal stimuli. The three classical methods a" histogram, sine wave fitting, and spectral analysis a" are thoroughly described, and new approaches are proposed to circumvent some of their limitations.

This is a must-have compendium, which can be used by both academics and test professionals to understand the fundamental mathematics underlining the algorithms of ADC testing, and as an handbook to help the engineer in the most important and critical details for their implementation.

The Analogue-to-digital converter (ADC) is the most pervasive block in electronic systems. With the advent of powerful digital signal processing and digital communication techniques, ADCs are fast becoming critical components for system's performance and flexibility. Knowing accurately all the parameters that characterise their dynamic behaviour is crucial, on one hand to select the most adequate ADC architecture and characteristics for each end application, and on the other hand, to understand how they affect performance bottlenecks in the signal processing chain.

Dynamic Characterisation of Analogue-to-Digital Converters presents a state of the art overview of the methods and procedures employed for characterising ADCs' dynamic performance behaviour using sinusoidal stimuli. The three classical methods - histogram, sine wave fitting, and spectral analysis - are thoroughly described, and new approaches are proposed to circumvent some of their limitations.

This is a must-have compendium, which can be used by both academics and test professionals to understand the fundamental mathematics underlining the algorithms of ADC testing, and as an handbook to help the engineer in the most important and critical details for their implementation.