Academic literature on the topic 'Sigma-Delta quantization'

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Journal articles on the topic "Sigma-Delta quantization"

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He, N., F. Kuhlmann, and A. Buzo. "Multiloop sigma-delta quantization." IEEE Transactions on Information Theory 38, no. 3 (May 1992): 1015–28. http://dx.doi.org/10.1109/18.135642.

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Benedetto, J. J., A. M. Powell, and O. Yilmaz. "Sigma-delta (/spl Sigma//spl Delta/) quantization and finite frames." IEEE Transactions on Information Theory 52, no. 5 (May 2006): 1990–2005. http://dx.doi.org/10.1109/tit.2006.872849.

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Hirai, Yusaku, Shinya Yano, and Toshimasa Matsuoka. "A Delta-Sigma ADC with Stochastic Quantization." IPSJ Transactions on System LSI Design Methodology 8 (2015): 123–30. http://dx.doi.org/10.2197/ipsjtsldm.8.123.

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Sidor, Tadeusz. "METROLOGICAL PROPERTIES OF A/D CONVERTERS UTILIZING HIGHER ORDER SIGMA–DELTA MODULATORS COMPARED WITH A/D CONVERTERS WITH MODULATORS OF FIRST ORDER." Metrology and Measurement Systems 21, no. 1 (March 1, 2014): 37–46. http://dx.doi.org/10.2478/mms-2014-0004.

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Abstract Time domain analysis is used to determine whether A/D converters that employ higher order sigma-delta modulators, widely used in digital acoustic systems, have superior performance over classical synchronous A/D converters with modulators of first order when taking into account their important metrological property which is the magnitude of the quantization error. It is shown that the quantization errors of delta-sigma A/D converters with higher order modulators are exactly on the same level as for converters with a first order modulator.
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Zierhofer, C. M. "Adaptive sigma-delta modulation with one-bit quantization." IEEE Transactions on Circuits and Systems II: Analog and Digital Signal Processing 47, no. 5 (May 2000): 408–15. http://dx.doi.org/10.1109/82.842109.

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Ostergaard, Jan, and Ram Zamir. "Multiple-Description Coding by Dithered Delta–Sigma Quantization." IEEE Transactions on Information Theory 55, no. 10 (October 2009): 4661–75. http://dx.doi.org/10.1109/tit.2009.2027528.

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Güntürk, C. Si̇nan. "One-bit sigma-delta quantization with exponential accuracy." Communications on Pure and Applied Mathematics 56, no. 11 (July 10, 2003): 1608–30. http://dx.doi.org/10.1002/cpa.3044.

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Lv, Bing Jun, Peng Fei Wang, Dong Bo Wang, Jun'an Liu, and Xiao Wei Liu. "A High-Performance Closed-Loop Fourth-Order Sigma-Delta Micro-Machined Accelerometer." Key Engineering Materials 503 (February 2012): 134–38. http://dx.doi.org/10.4028/www.scientific.net/kem.503.134.

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In this paper a high-performance closed-loop fourth-order sigma-delta (ΣΔ) micro-accelerometer is presented. After a introduction of sigma-delta accelerometer, system-level analysis and design of a fourth-order sigma-delta micro-accelerometer is given. The simulation result shows that an accelerometer with 107dB signal to noise ratio (SNR) and 17.5 bits effective number of bits (ENOB) is achieved. Through the root locus analysis, it is got that accelerometer is stable when quantization gain is bigger than 0.262. The accelerometer gets a good linearity and it becomes overload when input signal level is greater than -5dBFS.
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Callegari, Sergio, Federico Bizzarri, and Angelo Brambilla. "Optimal Coefficient Quantization in Optimal-NTF $\Delta \!\Sigma $ Modulators." IEEE Transactions on Circuits and Systems II: Express Briefs 65, no. 5 (May 2018): 542–46. http://dx.doi.org/10.1109/tcsii.2018.2821368.

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De Maeyer, Jeroen, Pieter Rombouts, and Ludo Weyten. "Efficient Multibit Quantization in Continuous-Time $\Sigma \Delta$ Modulators." IEEE Transactions on Circuits and Systems I: Regular Papers 54, no. 4 (April 2007): 757–67. http://dx.doi.org/10.1109/tcsi.2007.890607.

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Dissertations / Theses on the topic "Sigma-Delta quantization"

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Ayaz, Ulaş. "Sigma-delta quantization and Sturmian words." Thesis, University of British Columbia, 2009. http://hdl.handle.net/2429/14203.

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In this thesis, our main focus is Sigma-Delta quantization schemes. These are commonly used in state-of-art Analog-to-digital conversion technology. Their main advantage is the ease of implementation and more importantly their insensitivity to certain circuit imperfections. When we compare sigma-delta scheme with pulse-code modulation (PCM), sigma-delta is inferior in terms of rate distortion because an N-bit kth order sigma-delta quantizer produces an approximation with the error of order O(N-k) whereas the corresponding N-bit PCM scheme has accuracy of O(2−N)). However, this is a raw estimate of the actual rate-distortion characteristic of sigma-delta as one can further compress the bitstreams obtained via sigma-delta quantization. Even though this observation was made earlier in [10] under certain assumptions, to our knowledge, it was not investigated fully. In this thesis, such an investigation is made for first-order sigma-delta quantizers by using some results from symbolic dynamics literature on “Sturmian words”. Surprisingly, it turns out that the approximation error is a function of the “actual bit-rate”, i.e., the bit-rate after compressing an N-bit first-order sigma-delta encoding. In addition, in this thesis, we will introduce a new setup for sampling a bandlimited function and then quantizing these samples via first-order sigma-delta scheme. This simple but surprisingly efficient technique will allow us to get a better bound for the approximation rate of sigma-delta schemes and it will allow us to apply the derived results for compression of the bitstreams.
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Tangboondouangjit, Aram. "Sigma-Delta quantization number theoretic aspects of refining quantization error /." College Park, Md. : University of Maryland, 2006. http://hdl.handle.net/1903/3793.

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Thesis (Ph. D.) -- University of Maryland, College Park, 2006.
Thesis research directed by: Mathematics. Title from t.p. of PDF. Includes bibliographical references. Published by UMI Dissertation Services, Ann Arbor, Mich. Also available in paper.
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Zichy, Michael Andrew. "[Sigma Delta] Quantization with the hexagon norm in C /." Electronic version (PDF), 2006. http://dl.uncw.edu/etd/2006/zichym/michaelzichy.pdf.

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Galton, Ian Posner Edward C. Posner Edward C. "An analysis of quantization noise in delta sigma modulation and its application to parallel delta sigma modulation /." Diss., Pasadena, Calif. : California Institute of Technology, 1992. http://resolver.caltech.edu/CaltechETD:etd-07202007-150751.

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Neitola, M. (Marko). "Characterizing and minimizing spurious responses in Delta-Sigma modulators." Doctoral thesis, Oulun yliopisto, 2012. http://urn.fi/urn:isbn:9789514297496.

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Abstract Oversampling data converters based on Delta-Sigma modulation are a popular solution for modern high-resolution applications. In the design of digital-to-analog or analog-to-digital Delta-sigma converters there are common obstacles due to the difficulties on predicting and verifying their performance. Being a highly nonlinear system, a Delta-Sigma modulator’s (DSM) quantization noise and therefore the spurious tones are difficult to analyze and predict. Multi-bit DACs can be used to improve the performance and linearize the behavior of DSMs. However, this will give rise to the need for linearizing the multi-bit DAC. A popular DAC linearization method, data weighted averaging (DWA) shapes the DAC mismatch noise spectrum. There are many variants of DWA, for low-pass and band-pass DSMs. This thesis proposes a generalization which integrates a few published variants into one, broader DWA scheme. The generalization enables expanding the tone-suppression studies into a larger concept. The performance of one- or multibit DSMs is usually verified by simulations. This thesis proposes a simulation-based qualification (characterization) method that can be used to repeatedly verify and compare the performance of multibit DSM with a DAC mismatch shaping or scrambling scheme. The last contribution of this thesis is a very simple model for tonal behavior. The model enables accurate prediction of spurious tones from both DSMs and DWA-DACs. The model emulates the tone behavior by its true birth-mechanism: frequency modulation. The proposed prediction model for tone-behavior can be used for developing new tone-cancelation methods. Based on the model, a DWA linearization method is also proposed
Tiivistelmä Delta-Sigma modulaatio on suosituin tekniikka ylinäytteistävissä datan muuntimissa. Riippumatta toteutustarkoituksesta (analogia-digitaali- tai digitaali-analogia-muunnos), Delta-Sigma (DS) modulaatiossa on yleisesti tunnettuja käyttäytymisen ennustamiseen liittyviä ongelmia. Nämä ongelmat ovat peräisin modulaattorin luontaisesta epälineaarisuudesta: DS-muunnin on nimittäin vahvasti epälineaarinen takaisinkytketty systeemi, jonka harhatoistojen ennustaminen ja analysointi on erittäin hankalaa. Yksibittisestä monibittiseen DS-muuntimeen siirryttäessä muuntimen suorituskyky paranee, ja muuntimen kohinakäyttäytyminen on lineaarisempaa. Tämä kuitenkin kostautuu tarpeena linearisoida DS-muuntimen digitaali-analogia (D/A) muunnin. Tällä hetkellä tunnetuin linearisointimenetelmä on nimeltään DWA (data weighted averaging) algoritmi. Tässä työssä DWA:lle ja sen lukuisille varianteille esitellään eräänlainen yleistys, jonka avulla algoritmia voidaan soveltaa sekä alipäästö- että kaistanpäästö-DS-muuntimelle. Kuten tunnettua, DS-modulaattorin analyyttinen tarkastelu on raskasta. Yksi- ja monibittisten DS-muuntimien suunnitellun käyttäytymisen varmistaminen tapahtuukin yleensä simulointien avulla. Työssä esitetään simulointiperiaate, jolla voidaan kvalifioida (karakterisoida) monibittinen DS-muunnin. Tarkemmin, kvalifioinnin kohteena on DWA:n kaltaiset D/A -muuntimien linearisointimentelmät. Kyseessä on pyrkimys ennen kaikkea toistettavaan menetelmään, jolla eri menetelmiä voidaan verrata nopeasti ja luotettavasti. Tämän väitöstyön viimeinen kontribuutio on matemaattinen malli harhatoistojen syntymekanismille. Mallilla sekä DS-muunnoksen että DWA-D/A -muunnokseen liittyvät harhatoistot voidaan ennustaa tarkasti. Harhatoistot mallinnetaan yksinkertaisella havaintoihin perustuvalla FM-modulaatiokaavalla. Syntymekanismin mallinnus mahdollistaa DS-muuntimien ennustettavuuden ja täten auttaa harhatoiston kumoamismenetelmien kehittämistä. Työssä esitetään yksi matemaattisen mallin avulla kehitetty DWA-D/A -muunnoksen linearisointimenetelmä
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Syed, Arsalan Jawed. "Analog-to-Digital Converter Design for Non-Uniform Quantization." Thesis, Linköping University, Department of Electrical Engineering, 2004. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-2654.

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The thesis demonstrates a low-cost, low-bandwidth and low-resolution Analog-to- Digital Converter(ADC) in 0.35 um CMOS Process. A second-order Sigma-Delta modulator is used as the basis of the A/D Converter. A Semi-Uniform quantizer is used with the modulator to take advantage of input distributions that are dominated by smaller-amplitude signals e.g. Audio, Voice and Image-sensor signals. A Single-bit feedback topology is used with a multi-bit quantizer in the modulator. This topology avoids the use of a multi-bit DAC in the feedback loop – hence the system does not need to use digital correction techniques to compensate for a multi-bit DAC nonlinearity.

High-Level Simulations of the second-order Sigma-Delta modulator single-bit feedback topology along with a Semi-Uniform quantizer are performed in Cadence. Results indicate that a 5-bit Semi-Uniform quantizer with a Over-Sampling Ratio of 32, can achieve a resolution of 10 bits, in addition, a semi-uniform quantizer exhibits a 5-6 dB gain in SNR over its uniform counterpart for input amplitudes smaller than –10 dB. Finally, this system is designed in 0.35um CMOS process.

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Nordick, Brent C. "Dynamic Element Matching Techniques For Delta-Sigma ADCs With Large Internal Quantizers." Diss., CLICK HERE for online access, 2004. http://contentdm.lib.byu.edu/ETD/image/etd466.pdf.

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Penrod, Logan B. "An Exploratory Study of Pulse Width and Delta Sigma Modulators." DigitalCommons@CalPoly, 2020. https://digitalcommons.calpoly.edu/theses/2278.

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This paper explores the noise shaping and noise producing qualities of Delta-Sigma Modulators (DSM) and Pulse-Width Modulators (PWM). DSM has long been dominant in the Delta Sigma Analog-to-Digital Converter (DSADC) as a noise-shaped quantizer and time discretizer, while PWM, with a similar self oscillating structure, has seen use in Class D Power Amplifiers, performing a similar function. It has been shown that the PWM in Class D Amplifiers outperforms the DSM [1], but could this advantage be used in DSADC use-cases? LTSpice simulation and printed circuit board implementation and test are used to present data on four variations of these modulators: The DSM, PWM, the out-of-loop discretized PWM (OOLDP), and the cascaded modulator. A generic form of an Nth order loop filter is presented, where three orders of this generic topology are analyzed in simulation for each modulator, and two orders are used in physical testing.
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Cheng, Yongjie. "Design and Realization of a Single Stage Sigma-Delta ADC With Low Oversampling Ratio." Diss., CLICK HERE for online access, 2006. http://contentdm.lib.byu.edu/ETD/image/etd1561.pdf.

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Shang, Lei, and lei shang@ieee org. "Modelling of Mobile Fading Channels with Fading Mitigation Techniques." RMIT University. Electrical and Computer Engineering, 2006. http://adt.lib.rmit.edu.au/adt/public/adt-VIT20061222.113303.

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This thesis aims to contribute to the developments of wireless communication systems. The work generally consists of three parts: the first part is a discussion on general digital communication systems, the second part focuses on wireless channel modelling and fading mitigation techniques, and in the third part we discuss the possible application of advanced digital signal processing, especially time-frequency representation and blind source separation, to wireless communication systems. The first part considers general digital communication systems which will be incorporated in later parts. Today's wireless communication system is a subbranch of a general digital communication system that employs various techniques of A/D (Analog to Digital) conversion, source coding, error correction, coding, modulation, and synchronization, signal detection in noise, channel estimation, and equalization. We study and develop the digital communication algorithms to enhance the performance of wireless communication systems. In the Second Part we focus on wireless channel modelling and fading mitigation techniques. A modified Jakes' method is developed for Rayleigh fading channels. We investigate the level-crossing rate (LCR), the average duration of fades (ADF), the probability density function (PDF), the cumulative distribution function (CDF) and the autocorrelation functions (ACF) of this model. The simulated results are verified against the analytical Clarke's channel model. We also construct frequency-selective geometrical-based hyperbolically distributed scatterers (GBHDS) for a macro-cell mobile environment with the proper statistical characteristics. The modified Clarke's model and the GBHDS model may be readily expanded to a MIMO channel model thus we study the MIMO fading channel, specifically we model the MIMO channel in the angular domain. A detailed analysis of Gauss-Markov approximation of the fading channel is also given. Two fading mitigation techniques are investigated: Orthogonal Frequency Division Multiplexing (OFDM) and spatial diversity. In the Third Part, we devote ourselves to the exciting fields of Time-Frequency Analysis and Blind Source Separation and investigate the application of these powerful Digital Signal Processing (DSP) tools to improve the performance of wireless communication systems.
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Books on the topic "Sigma-Delta quantization"

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Yang, Yaohua. Effects and compensation of the analog integrator nonidealities in dual-quantization delta-sigma modulators. 1993.

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Book chapters on the topic "Sigma-Delta quantization"

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van Engelen, Jurgen, and Rudy van de Plassche. "Quantization and Sampling." In Bandpass Sigma Delta Modulators, 5–17. Boston, MA: Springer US, 1999. http://dx.doi.org/10.1007/978-1-4757-4586-3_2.

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Jiang, Jiayi, and Alexander M. Powell. "Sigma-Delta Quantization for Fusion Frames and Distributed Sensor Networks." In Frames and Other Bases in Abstract and Function Spaces, 101–24. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-55550-8_6.

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Liu, Qiyuan, Alexander Edward, Carlos Briseno-Vidrios, and Jose Silva-Martinez. "MASH 2-2 CTΔΣM with Fully Integrated Quantization Noise Leakage Calibration." In Design Techniques for Mash Continuous-Time Delta-Sigma Modulators, 101–27. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-77225-7_6.

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Liu, Qiyuan, Alexander Edward, Carlos Briseno-Vidrios, and Jose Silva-Martinez. "MASH 4-0 CTΔΣM with Fully Digital Quantization Noise Reduction Algorithm." In Design Techniques for Mash Continuous-Time Delta-Sigma Modulators, 129–57. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-77225-7_7.

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Bietti, Ivan, Guido Albasini, Enrico Temporiti, and Rinaldo Castello. "A 19mW 2.2GHz Fully Integrated CMOS Sigma Delta Fractional Synthesiser With 35Hz Frequency Step and Quantization Noise Compensation." In Analog Circuit Design, 77–96. Boston, MA: Springer US, 2003. http://dx.doi.org/10.1007/0-306-48707-1_4.

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"Quantization Noise Spectra." In Oversampling Delta-Sigma Data Converters, 81–105. IEEE, 2009. http://dx.doi.org/10.1109/9780470545461.ch6.

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"Quantization Noise in A/D Converters." In Delta-Sigma Data Converters. IEEE, 2009. http://dx.doi.org/10.1109/9780470544358.ch2.

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"Quantization Errors and Dithering in Modulators." In Delta-Sigma Data Converters. IEEE, 2009. http://dx.doi.org/10.1109/9780470544358.ch3.

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"The Structure of Quantization Noise from SigmaDelta Modulation." In Oversampling Delta-Sigma Data Converters, 52–59. IEEE, 2009. http://dx.doi.org/10.1109/9780470545461.ch3.

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Conference papers on the topic "Sigma-Delta quantization"

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Gunturk, C. Sinan, Mark Lammers, Alex Powell, Rayan Saab, and Ozgur Yilmaz. "Sigma delta quantization for compressed sensing." In 2010 44th Annual Conference on Information Sciences and Systems (CISS 2010). IEEE, 2010. http://dx.doi.org/10.1109/ciss.2010.5464825.

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Boufounos, Petros, and Richard G. Baraniuk. "Sigma delta quantization for compressive sensing." In Optical Engineering + Applications, edited by Dimitri Van De Ville, Vivek K. Goyal, and Manos Papadakis. SPIE, 2007. http://dx.doi.org/10.1117/12.734880.

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Hagiwara, Mao, Toru Kitayabu, Hiroyasu Ishikawa, and Hiroshi Shirai. "Delta-sigma modulator with non-uniform quantization." In 2011 IEEE Radio and Wireless Symposium (RWS). IEEE, 2011. http://dx.doi.org/10.1109/rws.2011.5725439.

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Ostergaard, Jan, and Ram Zamir. "Multiple-Description Coding by Dithered Delta-Sigma Quantization." In 2007 Data Compression Conference (DCC'07). IEEE, 2007. http://dx.doi.org/10.1109/dcc.2007.57.

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Costa, Laryssa L. O., Jose E. G. Medeiros, Jose A. A. de Andrade, and Sandro A. P. Haddad. "Nonlinear Quantization Technique for Multibit Sigma-Delta Modulators." In 2020 18th IEEE International New Circuits and Systems Conference (NEWCAS). IEEE, 2020. http://dx.doi.org/10.1109/newcas49341.2020.9159816.

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Abdelkefi, Fatma. "Sigma-Delta Quantization of Geometrically Uniform Finite Frames." In 2007 IEEE International Conference on Acoustics, Speech, and Signal Processing. IEEE, 2007. http://dx.doi.org/10.1109/icassp.2007.367130.

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Benedetto, J. J., and O. Oktay. "PCM - Sigma delta comparison and sparse representation quantization." In 42nd Annual Conference on Information Sciences and Systems (CISS 2008). IEEE, 2008. http://dx.doi.org/10.1109/ciss.2008.4558619.

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Li, Li, and Yudong Chen. "Quantization errors of modulo sigma-delta modulated ARMA processes." In 2013 IEEE China Summit and International Conference on Signal and Information Processing (ChinaSIP). IEEE, 2013. http://dx.doi.org/10.1109/chinasip.2013.6625303.

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Mashiach, Adam, Jan Ostergaard, and Ram Zamir. "Multiple description Delta-Sigma quantization with individual and central receivers." In 2010 IEEE 26th Convention of Electrical & Electronics Engineers in Israel (IEEEI 2010). IEEE, 2010. http://dx.doi.org/10.1109/eeei.2010.5661937.

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Delchamps, D. F. "Quantization noise in sigma-delta modulations driven by deterministic inputs." In [Proceedings] ICASSP-92: 1992 IEEE International Conference on Acoustics, Speech, and Signal Processing. IEEE, 1992. http://dx.doi.org/10.1109/icassp.1992.226345.

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