Bipolar biasing in high accuracy optical linear algebra processors

Casasent, David P.; Perlee, Caroline J.

doi:10.1364/ao.25.001033

Cited by 3 publications

(1 citation statement)

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“…In this case it is inevitable to encounter bipolar data. Until now, all the suggested methods to encode bipolar numbers can be divided into three categories: 112 biasing, 16 122 separating positive and negative numbers with multiplexing techniques such as time multiplexing, 17 space and frequency multiplexing, 18 and 132 bipolar number representation. [19][20][21][22] For high-speed computation the third class is optimal because the architecture may be a fully parallel one; in addition, it needs no data correction, no storage and combination of the intermediate result, and thus the least preprocessing and postprocessing.…”

Section: Introductionmentioning

confidence: 99%

Modified direct twos-complement parallel array multiplication algorithm for complex matrix operation

Liu

Shao

et al. 1995

Appl. Opt.

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A direct twos-complement parallel array multiplication algorithm is introduced and modified for digital optical numerical computation. The modified version overcomes the problems encountered in the conventional optical twos-complement algorithm. In the array, all the summands are generated in parallel, and the relevant summands having the same weights are added simultaneously without carries, resulting in the product expressed in a mixed twos-complement system. In a two-stage array, complex multiplication is possible with using four real subarrays. Furthermore, with a three-stage array architecture, complex matrix operation is straightforwardly accomplished. In the experiment, parallel two-stage array complex multiplication with liquid-crystal panels is demonstrated.

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Section: Introductionmentioning

confidence: 99%

Modified direct twos-complement parallel array multiplication algorithm for complex matrix operation

Liu

Shao

et al. 1995

Appl. Opt.

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Optical Linear Algebra Processors

Casasent

Kumar

1987

Optical Signal Processing

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Composite matched filter output partitioning

et al. 1987

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A common pattern recognition problem is finding a library element closest, in some sense, to a given reception.In many scenarios, optimaldetection requires Nmatched filters forNlibrary elements. Since Ncan often be quite large, there is a need for suboptimal techniques that base their decisions on a reduced number of filters.The use of composite matched filters (CMFs) (also called synthetic discriminant functions or linear combination filters) is one technique to achieve this reduction. For two level CMF outputs, the reduction is from Nto log 2 N matched filters. Previously, the coefficients of the CMF output were restricted to positive valuesoften 0 and 1. We refer to such filters as binary CMFs. An alternative approach is to use-land +1 for filter coefficients. This alternative filter will be called a bipolar CMF. This paper demonstrates how the extension from a binary to a bipolar CMF greatly improves the detection performance while still maintaining the reduced computational requirements of the binary CMF. Furthermore, the bipolar CMF is invariant to scale: multiplying the inputb a positive constant gives the same processor output. This desirable behavior does not exist for the binary CMF.

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Bipolar biasing in high accuracy optical linear algebra processors

Cited by 3 publications

References 3 publications

Modified direct twos-complement parallel array multiplication algorithm for complex matrix operation

Modified direct twos-complement parallel array multiplication algorithm for complex matrix operation

Optical Linear Algebra Processors

Composite matched filter output partitioning

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