The effects of aperture jitter and clock jitter in wideband ADCs

Löhning, Michael; Fettweis, Gerhard

doi:10.1016/j.csi.2005.12.005

Cited by 37 publications

(37 citation statements)

References 8 publications

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“…Using (4) leads to (6) In [17], the amount of overdrive to use in order to minimize the error in the estimation of the transition voltages due to additive noise was studied. There, an expression for the computation of the expected value of the transition voltages estimated with the Histogram Method has been derived, (7) where U k and σ n are the normalized values of transition voltage and additive noise standard deviation.…”

Section: Derivation Of the Estimation Biasmentioning

confidence: 99%

“…This method allows the estimation of different ADC parameters, namely the transition voltages, code bin widths integral non-linearity, differential nonlinearity, gain, and offset error. The estimators for these parameters are affected by the nonideal effects of the test setup or in the ADC itself, among which are additive noise [3]- [5], phase noise and jitter [6]- [8], stimulus signal distortion [3], and frequency error [9], [10].…”

Section: Introductionmentioning

confidence: 99%

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On the Bias of Terminal Based Gain and Offset Estimation Using the ADC Histogram Test Method

Alegria¹,

Tiglao²

2011

Metrology and Measurement Systems

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The Histogram Test method is a popular technique in analog-to-digital converter (ADC) testing. The presence of additive noise in the test setup or in the ADC itself can potentially affect the accuracy of the test results. In this study, we demonstrate that additive noise causes a bias in the terminal based estimation of the gain but not in the estimation of the offset. The estimation error is determined analytically as a function of the sinusoidal stimulus signal amplitude and the noise standard deviation. We derive an exact but computationally difficult expression as well as a simpler closed form approximation that provides an upper bound of the bias of the terminal based gain. The estimators are validated numerically using a Monte Carlo procedure with simulated and experimental data.

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Section: Derivation Of the Estimation Biasmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

On the Bias of Terminal Based Gain and Offset Estimation Using the ADC Histogram Test Method

Alegria¹,

Tiglao²

2011

Metrology and Measurement Systems

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“…This filter is usually modeled as a lowpass filter whose cutoff frequency is called the loop bandwidth. The effect of timing noise on the observation is often modeled as signalindependent additive white Gaussian noise (AWGN) [2], [3]. However, when viewed as an additive noise, the effect of timing noise is not signal independent and furthermore neither white nor Gaussian.…”

Section: Introductionmentioning

confidence: 99%

Delay Estimation in the Presence of Timing Noise

Kusuma

Goyal

2008

IEEE Trans. Circuits Syst. II

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“…The noise distribution resembles a Random Walk and is termed Brown Noise as its samples resemble Brownian Motion [12]. It can be modeled as a Wiener Process [5] The auto-correlation function of independent jitter is an impulse function and that for accumulated jitter approximates a triangular function as demonstrated in Fig. 1 and Fig.…”

Section: Non-uniform Samplingmentioning

confidence: 99%

“…The former is termed aperture jitter and is caused by thermal noise in the S/H circuit. It is commonly modeled as an independent White Gaussian process [5], [6] and [7]. Accumulated clock jitter is caused by the phase noise of the oscillator and is modeled as a Wiener Process [1], [5], [8].…”

Section: Introductionmentioning

confidence: 99%