AD677

REV. A

–12–

AC PERFORMANCE

AC parameters, which include S/(N+D), THD, etc., reflect the

AD677’s effect on the spectral content of the analog input sig-

nal. Figures 11 through 18 provide information on the AD677’s

ac performance under a variety of conditions.

A perfect n-bit ADC with no errors will yield a theoretical quan-

tization noise of q/

√12, where q is the weight of the LSB. This

relationship leads to the well-known equation for theoretical

full-scale rms sine wave signal-to-noise plus distortion level of

S/(N + D) = 6.02 n + 1.76 dB, here n is the bit resolution. An

actual ADC, however, will yield a measured S/(N + D) less than

the theoretical value. Solving this equation for n using the mea-

sured S/(N + D) value yields the equation for effective number

of bits (ENOB):

ENOB

=

S / N

+ D

()

[]

6.02

As a general rule, averaging the results from several conversions

reduces the effects of noise, and therefore improves such param-

eters as S/(N+D). AD677 performance may be optimized by

operating the device at its maximum sample rate of 100 kSPS

and digitally filtering the resulting bit stream to the desired sig-

nal bandwidth. This succeeds in distributing noise over a wider

frequency range, thus reducing the noise density in the fre-

quency band of interest. This subject is discussed in the follow-

ing section.

OVERSAMPLING AND NOISE FILTERING

The Nyquist rate for a converter is defined as one-half its sam-

pling rate. This is established by the Nyquist theorem, which

requires that a signal be sampled at a rate corresponding to at

least twice its highest frequency component of interest in order

to preserve the informational content. Oversampling is a conver-

sion technique in which the sampling frequency is more than

twice the frequency bandwidth of interest. In audio applications,

the AD677 can operate at a 2

× F

In quantized systems, the informational content of the analog

input is represented in the frequency spectrum from dc to the

Nyquist rate of the converter. Within this same spectrum are

higher frequency noise and signal components. Antialias, or low

pass, filters are used at the input to the ADC to reduce these

noise and signal components so that their aliased components

do not corrupt the baseband spectrum. However, wideband

noise contributed by the AD677 will not be reduced by the

antialias filter. The AD677 quantization noise is evenly distrib-

uted from dc to the Nyquist rate, and this fact can be used to

minimize its overall affect.

The AD677 quantization noise effects can be reduced by over-

sampling—sampling at a rate higher than that defined by the

Nyquist theorem. This spreads the noise energy over a band-

width wider than the frequency band of interest. By judicious

selection of a digital decimation filter, noise frequencies outside

the bandwidth of interest may be eliminated.

The process of analog to digital conversion inherently produces

noise, known as quantization noise. The magnitude of this noise

is a function of the resolution of the converter, and manifests it-

self as a limit to the theoretical signal-to-noise ratio achievable.

This limit is described by S/(N + D) = (6.02n + 1.76 + 10 log

interest. For audio bandwidth applications, the AD677 is ca-

pable of operating at a 2

× oversample rate (96 kSPS), which

typically produces an improvement in S/(N+D) of 3 dB com-

pared with operating at the Nyquist conversion rate of 48 kSPS.

Oversampling has another advantage as well; the demands on

the antialias filter are lessened. In summary, system perfor-

mance is optimized by running the AD677 at or near its maxi-

mum sampling rate of 100 kHz and digitally filtering the

resulting spectrum to eliminate undesired frequencies.

DC PERFORMANCE

The self-calibration scheme used in the AD677 compensates for

bit weight errors that may exist in the capacitor array. This mis-

match in capacitor values is adjusted (using the calibration coef-

ficients) during conversion and provides for excellent dc

linearity performance. Figure 19 illustrates the DNL plot of a

typical AD677 at +25

°C. A histogram test is a statistical method

for deriving an A/D converter’s differential nonlinearity. A ramp

input is sampled by the ADC and a large number of conversions

are taken and stored. Theoretically the codes would all be the

same size and, therefore, have an equal number of occurrences.

A code with an average number of occurrences would have a

DNL of “0”. A code with more or less than average will have a

DNL of greater than or less than zero LSB. A DNL of –1 LSB

indicates missing code (zero occurrences).

Figure 20 illustrates the code width distribution of the DNL

plots of Figure 19.

DC CODE UNCERTAINTY

Ideally, a fixed dc input should result in the same output code

for repetitive conversions. However, as a consequence of un-

avoidable circuit noise within the wideband circuits in the ADC,

there is range of output codes which may occur for a given input

voltage. If you apply a dc signal to the AD677 and record

10,000 conversions, the result will be a distribution of codes as

shown in Figure 9 (using a 10 V reference). If you fit a Gaussian

probability distribution to the histogram, the standard deviation

is approximately equivalent to the rms input noise of ADC.

1

–1

–2

DEVIATION FROM CORRECT CODE – LSBs

8000

0

2000

4000

6000

0

7000

5000

3000

1000

3

1267

7649

1081

Figure 9. Distribution of Codes from 10,000 Conversions

Relative to the Correct Code