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Correction of ADC Errors by Additive Iterative Method with Dithering

References Michaeli, L., Šaliga, J., Sochová, L. (2008). Integral nonlinearity correction algorithm based on error table optimizing and noise filtering. Measurement Science Review , 1 (2), 29-32. Muravyov, S. V. (2000). Model of procedure for measurement result error correction. In Proceedings of the XVI IMEKO World Congress , 25-28 September 2000. Hofburg, Vienna, Austria. CD-ROM. Kamenský, M. (2009). Contribution to Automatic Correction of ADC. (In Slovak). Doctoral

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A 10 GS/s time-interleaved ADC in 0.25 micrometer CMOS technology

R eferences [1] C. A. Schmidt, J. E. Cousseau, J. L. Figueroa, B. T. Reyes and M. R. Hueda, “Efficient Estimation and Correction of Mismatch Errors Time-Interleaved ADCs”, IEEE Transactions on Instrumentation and Measurement , vol. 65, no. 2, 2016, pp. 243–254. [2] D. R. Oh, J. I. Kim, M. J. Seo, J. G. Kim and S. T. Ryu, “A 6-bit 10 GS/s 63 mW 4x TI Time-Domain Interpolating Flash ADC 65 nm CMOS”, European Solid-State Circuits Conference (ESSCIRC), 2015, pp. 323–326. [3] Y. C. Chen, J. S. Lai and Z. M. Lin, “A 6Bit 3GS/s Two-Channel Time

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Measuring Static Parameters of Embedded ADC Core

Solid State Circuits 19 No. 6 (1984), 820-827. VANDEN BOSSCHE, M.—SCHOUKENS, J.—RENNEBOOG, J.: Dynamic Testing and Diagnostics of A/D Converters, IEEE Transactions on Circuits and Systems 33 No. 8 (1986), 775-785. WAGDY, M. F.—AWAD, S. S.: Determining ADC Effective Number of Bits via Histogram Testing, IEEE Transactions on Instrumentation and Measurement 40 No. 4 (1991), 770-772. CARBONE, P.—CHIORBOLI, G.: ADC Sinewave Histogram Testing with Quasi-Coherent Sampling, IEEE Transactions

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Frequency Selection of Sine Wave for Dynamic ADC Test

References IEEE Standards (2000). IEEE Standard for Terminology and Test Methods for Analog-to-Digital Converters. IEEE Std 1241-2000. IEEE Standards (2007). IEEE Standard for Digitizing Waveform Recorders. IEEE Std 1957-2007. (Revision of IEEE Std 1057-1994). Blair, J. J. (2005). Selecting test frequencies for sinewave tests of ADCs. IEEE Transactions On Instrumentation And Measurement , 54 (1), 73-78. Carbone, P., Petri, D. (2000). Effective

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A Method for ADC Error Testing and its Compensation in Ratiometric Measurements

References Bonnie Baker, Miro Oljaca, "How the voltage reference affects ADC performance Texas instruments "Data acquisition division". L. Michaeli, L. Sochová, and J. Saliga, "ADC look-up table based post correction combined with dithering," in XVIII IMEKO WORLD CONGRESS Rio de Janeiro, Brazil, 2006. N. Björsell and P. Händel, "Dynamic behavior models of analog to digital converters aimed for post-correction in wideband applications" in IMEKO World Congress, Rio de Janeiro, Brazil

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Retrieved cerebral thrombi studied by T 2 and ADC mapping: preliminary results

mechanical thrombectomy) is strongly influenced by thrombi permeability and their mechanical properties. 11 , 12 An accurate assessment of the thrombi structure and composition could be helpful in treatment planning and prognosis of recanalization. 13 , 14 Magnetic resonance imaging (MRI) is a sensitive tool for diagnosing ischemic stroke based on detecting water mobility in different tissue compartments. The detection is enabled by diffusion-weighted imaging (DWI) followed by a calculation of the apparent diffusion constant (ADC) map. 15 Another MRI mapping

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Iterative Method and Dithering with Averaging used for Correction of ADC Error

Iterative Method and Dithering with Averaging used for Correction of ADC Error

Additive iterative method in combination with averaging of dithered samples is designed for self-correction of ADC linearity error in the paper. Iterative method is one of the automated error correction techniques. Dithering is a special tool for quantizer performance enhancement. Dither theory for Gaussian noise and averaging has been used for exhibition of method abilities in ADC characteristic improvement.

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Error Models of the Analog to Digital Converters

References [1] IEEE Std. (2008). IEEE Standard for digitizing waveform recorders. 1057-2007. New York: IEEE. [2] IEEE Std. (2011). IEEE Standard for terminology and test methods for analog-to-digital converters. 1241-2010. New York: IEEE. [3] Arpaia, P., Daponte, P., Michaeli, L. (1999). The influence of the architecture on ADC modelling. IEEE Transactions on Instrumentation and Measurement, 48(5), 956-967. [4] Alegria, F., Arpaia, P., Daponte, P., Serra, A.C. (2002). An ADC histogram test based

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Integrated Attitude and Navigation System for Small Airplane

Abstract

Navigation system is one of the most important aircraft systems. Accuracy and precision of position and attitude is extremely important for safe aircraft operations. The integrated INS/GNSS systems are commonly used as autonomous on-board devices for fulfilling this task. The INS sensors like accelerometers and gyroscopes are mainly affected by drift. The GNSS encounter stochastic disturbances with no tendency to grow in time but as each radio navigation system may be jammed or its signal can just be not available. These base properties of errors make these two systems well suited for integration. These were the main motivations for development of integrated navigation and attitude determination system, presented in this article. In the developed system, data is integrated from all available sensors, particularly INS, GPS, and air data computer. Navigation information from these sensors is combined using Kalman filtering algorithms to obtain robust solution, effective also in a case of failure/inaccessibility of GPS. Position calculated using the accelerations from INS is corrected by position from GPS and optionally by position calculated using the true airspeed (TAS) from ADC. Navigation system is modelled and programmed in MATLAB environment. The system was tested using the data from real experiments, proving efficiency of the method.

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On Measurement Uncertainty of ADC Nonlinearities in Oscillation-Based Test

On Measurement Uncertainty of ADC Nonlinearities in Oscillation-Based Test

Oscillation-based test (OBT) is one of the approaches for measuring static ADC parameters such as differential nonlinearity (DNL) and integral nonlinearity (INL) that can be implemented in a built-in self-test arrangement. When applying the OBT approach in practice we noticed an inherent measurement uncertainty related to the slope of the ADC input signal in OBT test mode. Experimental environment in Matlab has been set up to study the phenomenon. Experiments with varying values of slope were performed to demonstrate the margins of DNL measurement uncertainty.

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