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Proceedings ArticleDOI

Real-time compensation of static distortion by measurement of differential noise gain

18 Dec 2014-pp 1-5
TL;DR: This work characterises the distorting process and linearises the system in real-time using statistical measurements of the observed noise at the output of a cascaded system of amplifiers.
Abstract: It is well-known that in a cascaded system of amplifiers the majority of noise is due to the first stage and the majority of distortion due to the final stage. Consequently, the observed noise at the output is subject to the same nonlinear process as the signal of interest. We use this fact to characterise the distorting process and linearise the system in real-time using statistical measurements of this noise.
Citations
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Proceedings ArticleDOI
13 Jul 2016
TL;DR: A new technique for compensation of static nonlinear distortion using the internal noise of the device improves upon previous approaches by allowing highly-efficient fixed-point implementation, and represents the first step towards direct integration with analog hardware in order to produce an ADC that is blind to its analog frontend.
Abstract: In most designs, residual nonlinearity is considered an inescapable curse-even when it is known to be present, it is often assumed to be too unpredictable or unstable to be dealt with in postprocessing. However, with the aid of outputonly system identification, this is no longer the case. We have developed a new technique for compensation of static nonlinear distortion using the internal noise of the device. It improves upon previous approaches by allowing highly-efficient fixed-point implementation, and represents the first step towards direct integration with analog hardware in order to produce an ADC that is blind to its analog frontend.

1 citations


Cites background or methods from "Real-time compensation of static di..."

  • ...This could be some sort of deterministic signal, but in our experiments [11], [12] we have used the input noise of a common-emitter amplifier....

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  • ...We have previously described a technique [11] for the compensation of static nonlinearity using output-only measurements, and succeeded in refining the concept into an algorithm capable of operating in real-time on a microcontroller platform [12]....

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  • ...The unusual high-pass filtering approach is inherited from the arrangements in [12], where we required both high-pass and low-pass outputs....

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  • ...We present a technique here that can be efficiently implemented using fixed-point arithmetic without the need for either divisions or square-root operations as required by [12]....

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  • ...We overcame both of these problems in [12] by integrating a curve-fitted version of (f−1)′(x); a set of triangular radial basis functions were used to describe f ′(x), resulting in a piecewise-linear fitted curve, and a piecewise quadratic fit to the distorting function....

    [...]

Journal ArticleDOI
TL;DR: Nonlinearity in many systems is heavily dependent on component variation and environmental factors such as temperature, which limits the range over which the device will produce directly useful measurements, often to far less than the device's safe range of operation.
Abstract: Nonlinearity in many systems is heavily dependent on component variation and environmental factors such as temperature. This is often overcome by keeping signals close enough to the device's operating point that it appears approximately linear. But as the signal being measured becomes larger, the deviation from linearity increases, and the device's nonlinearity specification will be exceeded. This limits the range over which the device will produce directly useful measurements, often to far less than the device's safe range of operation.

Cites background from "Real-time compensation of static di..."

  • ...Total harmonic distortion before and after compensation of a distorted sinusoid with the device presented in and as measured in [2], as a function of distortion level and signal frequency (© 2014 IEEE)....

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References
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Book
01 Jan 1987
TL;DR: Das Buch behandelt die Systemidentifizierung in dem theoretischen Bereich, der direkte Auswirkungen auf Verstaendnis and praktische Anwendung der verschiedenen Verfahren zur IdentifIZierung hat.
Abstract: Das Buch behandelt die Systemidentifizierung in dem theoretischen Bereich, der direkte Auswirkungen auf Verstaendnis und praktische Anwendung der verschiedenen Verfahren zur Identifizierung hat. Da ...

20,436 citations


"Real-time compensation of static di..." refers background in this paper

  • ...Techniques exist [2] to identify nonlinear systems, but these rely on knowledge—or even control—of the system input, and are therefore inappropriate in cases where the system cannot be calibrated, or where the nonlinearity varies with time....

    [...]

Journal ArticleDOI
TL;DR: This paper gives a selective but up-to-date survey of several recent developments that explains their usefulness from the theoretical point of view and contributes useful new classes of radial basis function.
Abstract: From the Publisher: "In many areas of mathematics, science and engineering, from computer graphics to inverse methods to signal processing it is necessary to estimate parameters, usually multidimensional, by approximation and interpolation. Radial basis functions are a modern and powerful tool which work well in very general circumstances, and so are becoming of widespread use, as the limitations of other methods, such as least squares, polynomial interpolation or wavelet-based, become apparent." This is the first book devoted to the subject and the author's aim is to give a thorough treatment from both the theoretical and practical implementation viewpoints. For example, he emphasises the many positive features of radial basis functions such as the unique solvability of the interpolation problem, the computation of interpolants, their smoothness and convergence, and provides a careful classification of the radial basis functions into types that have different convergence. A comprehensive bibliography rounds off what will prove a very valuable work.

1,335 citations

Book ChapterDOI
03 Oct 2018
TL;DR: This paper gives a selective but up-to-date survey of several recent developments that explains their usefulness from the theoretical point of view and contributes useful new classes of radial basis function.
Abstract: This chapter considers radial basis function (RBF) networks. A RBF network can be described as a parametrized model used to approximate an arbitrary function by means of a linear combination of basic functions. RBF networks belong to the class of kernel function networks where the inputs to the model are passed through kernel functions which limit the response of the network to a local region in the input space for each kernel or basis function. The chapter describes learning algorithms for RBF networks and shows how they can overcome the problem of training that normally occurs in multilayer networks. It explores the use of RBF networks in terms of basic theory, architectures, learning algorithms, and applications to signal processing. An interesting relationship that can be drawn between RBF networks and probabilistic framework is that when a Gaussian basis function is used, the model can be viewed as a mixture of normal density functions.

444 citations


"Real-time compensation of static di..." refers background in this paper

  • ...This term also includes harmonics of the signal being measured, and therefore greater accuracy is achievable in systems with a wider noise bandwidth that extends beyond the measurable distortion products of the signal....

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Journal ArticleDOI
06 Jul 1998
TL;DR: A broadband variant of the histogram test where Gaussian noise is used as a stimulus signal is presented and tolerance and confidence intervals are determined both for the integral nonlinearity (INL) and differential non linearity (DNL) vectors, related to the number of samples acquired.
Abstract: A broadband variant of the histogram test where Gaussian noise is used as a stimulus signal is presented. A methodology allowing for an automated and extensive characterization of analog-to-digital converters (ADCs) is given. Tolerance and confidence intervals are determined both for the integral nonlinearity (INL) and differential nonlinearity (DNL) vectors, related to the number of samples acquired. Experimental results of the characterization of a VXI waveform digitizer using this methodology are shown.

51 citations


"Real-time compensation of static di..." refers background in this paper

  • ...Some test signals include sinusoids [3], triangular signals [3], and Gaussian noise [4]....

    [...]

Book
01 May 2004
TL;DR: In this article, a detailed introduction to radio frequency (RF) engineering, using a straightforward and easily understood approach combined with numerous worked examples, illustrations, and homework problems, is provided for graduate students, researchers and practising engineers.
Abstract: Originally published in 2004, this book provides a detailed introduction to radio frequency (RF) engineering, using a straightforward and easily understood approach combined with numerous worked examples, illustrations and homework problems. The author focuses on minimising the mathematics needed to grasp the subject while providing a solid theoretical foundation for the student. Emphasis is also placed on the practical aspects of radio engineering. The book provides a broad coverage of RF systems, circuit design, antennas, propagation and digital techniques. It will provide an excellent introduction to the subject for graduate students, researchers and practising engineers.

28 citations