Floating-point signal processing-arithmetic, roundoff-noise, and limit cycles

Lacroix, A.

doi:10.1109/iscas.1988.15339

Cited by 12 publications

(2 citation statements)

References 33 publications

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“…However, only a small portion of this work was dedicated to the problem of describing the dynamic behavior deterministically [ 11- [9]. A more recent treatment of the stability and limit cycle problem can be found in [4], [6]- [9]. Practically all previous work addressed the case of a difference equation implementation with a single quantizer.…”

Section: Introductionmentioning

confidence: 99%

Absolute response error bounds for floating point digital filters in state space representation

Barr

Sellyey

1995

IEEE Trans. Circuits Syst. II

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The Advanced Photon Source (APS) at Argonne National Laboratory will be a 7-GeV machine. It is anticipated that for beam operations beyond the baseline design of 100 mA stored beam current, a ttansverse and longitudinal damping system is needed to damp instabilities. A key part of this digital damping system is digital signal processing. This digital system will be used to process samples taken from the beam and determine appropriate correction values to be applied to digid with adaptable filter Weigh@. beMHz. This paper concentrates on the digital processing involved in this system, and especially on the adaptive algorithms used for determining the digital filter weights.tunes and a third for the longitudinal tune. For APS the same digital transversal filter design can be used for all three tunes. This paper deals with the design of fdter coefficients. It is natural to use a single pickup for this type of system. One stripline can readily be used to measure the two transverse displacements and longitudinal phase of each bunch on each turn. Two turns of information can be used to calculate the kick which needs to be applied to the bunch in order to cancel its transverse velocity. Let be the displacement of a bunch on one turn. On the next turn (2) the beam. The processing will take the form of a transversaldone at 176 h4Hz with a possible correction bandwidth of 88 &e displacement will be y2 = A sin(2m + 4,), where v is the fractional tune. The transverse velocity of this bunch at the kicker will be

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Section: Introductionmentioning

confidence: 99%

Absolute response error bounds for floating point digital filters in state space representation

Barr

Sellyey

1995

IEEE Trans. Circuits Syst. II

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“…Previous tutorial on floating-point arithmetic in digital signal processing was written by Lacroix [40].…”

Section: Introductionmentioning

confidence: 99%

Floating-point arithmetic in signal processing

Kontro

Kalliojarvi

Neuvo

[Proceedings] 1992 IEEE International Symposium on Circuits and Systems

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The use of floating-point arithmetic in digital signal processing is considered in this paper. First, an introduction to floating-point arithmetic based on the IEEE floating-point standards is given. Then, finite wordlength effects of these arithmetic systems are presented. Finally floating-point hardware is discussed. Special emphasis in this paper is on audio applications. As an example, amplitude distributions and signal-to-noise ratios of quantized music are considered, and audio standards using floatingpoint arithmetic are presented. 1784 0-7803-0593-0/92 $3.00 1992 IEEE S.H. Ardalan, "Floating-point error analysis of recursive least-squares and least-mean-squares adaptive filters," IEEE %ns.

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Roundoff Noise in Floating Point Digital Filters

Rao

1996

Control and Dynamic Systems

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Floating-point signal processing-arithmetic, roundoff-noise, and limit cycles

Cited by 12 publications

References 33 publications

Absolute response error bounds for floating point digital filters in state space representation

Absolute response error bounds for floating point digital filters in state space representation

Floating-point arithmetic in signal processing

Roundoff Noise in Floating Point Digital Filters

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