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Nawab, S. Hamid; Oppenheim, Alan V.; Chandrakasan, Anantha P.; Winograd, Joseph M.; Ludwig, Julian

doi:10.1023/a:1007986707921

Cited by 95 publications

(7 citation statements)

References 49 publications

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“…For example, a paper with the title "Approximate signal processing" was published in 1997 [5]. However, new problems emerged in the last decade that stimulated new research in applying approximation techniques, but in a slightly different context than before.…”

Section: Approximate Computingmentioning

confidence: 99%

Approximate Circuits in Low-Power Image and Video Processing: The Approximate Median Filter

Sekanina¹,

Vašíček²,

Mrázek³

2017

RADIOENGINEERING

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Section: Approximate Computingmentioning

confidence: 99%

Approximate Circuits in Low-Power Image and Video Processing: The Approximate Median Filter

Sekanina¹,

Vašíček²,

Mrázek³

2017

RADIOENGINEERING

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“…A particularly interesting instance to illustrate this point is the concept of approximate DSP [35]. In this approach, the application specialist and the algorithm designer work hand in hand-they might even be the same person-to alter the algorithm to meet the needs of the signal processing application to achieve greater efficiencies.…”

Section: Engaging the Application Layer And The 'Line In The Sand' Mementioning

confidence: 99%

“…While our line in the sand might, in fact, seem to provide a clear divide between an exact and inexact computing paradigm, the domain of DSP has instances that, at first glance, seem to make this boundary somewhat fuzzy. A particularly interesting instance to illustrate this point is the concept of approximate DSP [35]. In this approach, the application specialist and the algorithm designer work hand in hand-they might even be the same person-to alter the algorithm to meet the needs of the signal processing application to achieve greater efficiencies.…”

Section: Engaging the Application Layer And The 'Line In The Sand' Metaphormentioning

confidence: 99%

Inexactness and a future of computing

Palem

2014

Phil. Trans. R. Soc. A.

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As pressures, notably from energy consumption, start impeding the growth and scale of computing systems, inevitably, designers and users are increasingly considering the prospect of trading accuracy or exactness . This paper is a perspective on the progress in embracing this somewhat unusual philosophy of innovating computing systems that are designed to be inexact or approximate , in the interests of realizing extreme efficiencies. With our own experience in designing inexact physical systems including hardware as a backdrop, we speculate on the rich potential for considering inexactness as a broad emerging theme if not an entire domain for investigation for exciting research and innovation. If this emerging trend to pursuing inexactness persists and grows, then we anticipate an increasing need to consider system co-design where application domain characteristics and technology features interplay in an active manner. A noteworthy early example of this approach is our own excursion into tailoring and hence co-designing floating point arithmetic units guided by the needs of stochastic climate models. This approach requires a unified effort between software and hardware designers that does away with the normal clean abstraction layers between the two.

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“…Digital filters represent a fundamental signal processing element which is found in all of the portable systems already mentioned and many others. Motivated by the growing demand for low power digital signal processing techniques for use in mobile devices, algorithmic approaches to low power frequency-selective digital filtering have been extensively developed [11][12][13][14][15][16][17][18][19][20]. It has been demonstrated that significant power savings may be achieved in digital filtering applications when the order of a digital filter is dynamically varied to provide time-varying stopband attenuation in proportion to the timevarying signal-to-noise ratio (SNR) of the input signal, while maintaining a fixed SNR at the filter output.…”

Section: Introductionmentioning

confidence: 99%

Low Power Digital Filtering Using Adaptive Approximate Processing: Fir Filter Structures

Ludwig

2021

Global J. Elec. Comp. Eng.

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Techniques for reducing power consumption in digital circuits have become increasingly important because of the growing demand for portable multimedia devices. Digital filters, being ubiquitous in such devices, are a prime candidate for low power design. Algorithmic approaches to low power frequency-selective digital filtering which are based on the concepts of adaptive approximate processing have been developed and formalized by introducing the class of approximate filtering algorithms in which the order of a digital filter is dynamically varied to provide time-varying stopband attenuation in proportion to the time-varying signal-to-noise ratio (SNR) of the input signal, while maintaining a fixed SNR at the filter output. Since power consumption in digital filter implementations is proportional to the order of the filter, dynamically varying the filter order is a strategy which may be used to conserve power. In this paper we introduce a class of approximate filter structures using FIR digital filter constituent elements. These filter structures are explored and shown to be an important element in the characterization of approximate filtering algorithms.

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Untitled

Cited by 95 publications

References 49 publications

Approximate Circuits in Low-Power Image and Video Processing: The Approximate Median Filter

Approximate Circuits in Low-Power Image and Video Processing: The Approximate Median Filter

Inexactness and a future of computing

Low Power Digital Filtering Using Adaptive Approximate Processing: Fir Filter Structures

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