Optical Signal Processing.

VanderLugt, A.

doi:10.21236/ada135908

Cited by 140 publications

(72 citation statements)

References 4 publications

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“…These included time integrating correlators [90] (architecturally simpler linear time variants of the constant time space integrating matched filter mentioned already) and systolic architectures [21]. In addition to pattern recognition, a common application for these classes of architectures was numerical calculation.…”

Section: Optical Pattern Recognitionmentioning

confidence: 99%

“…Matrix-vector and matrix-matrix multiplication systems were proposed and demonstrated [42,57,90,48,4,29,51]. The capability to expand a beam of light and to focus many beams of light to a common point directly corresponded to high fan-out and fan-in capabilities, respectively.…”

Section: Analog Optical Numerical Computationmentioning

confidence: 99%

“…Numerous physical implementations of the latter class exist, and example applications include fast pattern recognition and matrix-vector algebra [35,90]. There have been much resources devoted to designs, implementations and algorithms for such optical information processing architectures (for example see [4,15,29,35,52,55,57,62,77,90,101,27] and their references).…”

Section: Optical Models Of Computation and Computational Complexitymentioning

confidence: 99%

“…One could write to a SLM offline (expose photographic film, or laser print or relief etch a transparency) or online (in the case of a liquid-crystal display [102,62,91] or holographic material [24,74]). The functions h and v could be effected using two convex cylindrical lenses, oriented horizontally and vertically, respectively [90,35,62,34].…”

Section: Optical Realisationmentioning

confidence: 99%

“…This finite distance is called the focal length of the lens. The constant θ used in the definitions of h and v could be effected using Fourier spectrum size reduction techniques [90,35] such as varying the focal length of the lens, varying the separation of the lens and SLM, employing cascaded Fourier transformation, increasing the dimensions/reducing the spatial resolution of the SLM, or using light with a shorter wavelength.…”

Section: Optical Realisationmentioning

confidence: 99%

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Optical computing

Woods¹,

Naughton²

2009

Applied Mathematics and Computation

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We consider optical computers that encode data using images and compute by transforming such images. We give an overview of a number of such optical computing architectures, including descriptions of the type of hardware commonly used in optical computing, as well as some of the computational efficiencies of optical devices. We go on to discuss optical computing from the point of view of computational complexity theory, with the aim of putting some old, and some very recent, results in context. Finally, we focus on a particular optical model of computation called the continuous space machine. We describe some results for this model including characterisations in terms of well-known complexity classes.

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Section: Optical Pattern Recognitionmentioning

confidence: 99%

Section: Analog Optical Numerical Computationmentioning

confidence: 99%