Abstract

An optical bidirectional associative memory offering a potential of operating up to 106 neurons with 1012 interconnections is described. Except possibly for input and output all operations are optical and parallel.

© 1988 Optical Society of America

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References

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  1. B. Kosko, Ed., Image Understanding, Proc. Soc. Photo-Opt. Instrum. Eng.758 (Jan.1987).
  2. B. Kosko, “Competitive Adaptive Bidirectional Associative Memories,” in Proceedings, IEEE International Conference on Neural Networks (ICNN-1987), Vol. 2 (1987), pp. 759–766.
  3. B. Kosko, “Adaptive Bidirectional Associative Memories,” Appl. Opt. 26, 4947 (1987).
    [CrossRef] [PubMed]
  4. J. W. Goodman, A. R. Dias, L. M. Woody, “Fully Parallel, High Speed Incoherent Optical Method for Performing Discrete Fourier Transforms,” Opt. Lett. 2, 1 (1978).
    [CrossRef] [PubMed]
  5. B. Kosko, C. Guest, “Optical Bidirectional Associative Memories,” Proc. Soc. Photo-Opt. Instrum. Eng.758 (Jan.1987).
  6. N. H. Farhat, “Architectures for Optoelectronic Analogs of Self-organizing Neural Networks,” Opt. Lett. 12, 6 (1987).
    [CrossRef]
  7. H. J. Caulfield, “Parallel N4 Weighted Optical Interconnections,” Appl. Opt. 26, 4039 (1987).
    [CrossRef] [PubMed]
  8. J. Shamir, “Three-Dimensional Optical Interconnection Gate Array,” Appl. Opt. 26, 3455 (1987).
    [CrossRef] [PubMed]
  9. M. A. Handschy, K. M. Johnson, W. T. Cathey, L. A. Pagano-Stauffer, “Polarization-Based Optical Parallel Logic Gate Utilizing Ferroelectric Liquid Crystals,” Opt. Lett. 12, 611 (1987).
    [CrossRef] [PubMed]
  10. H. M. Gibbs, N. Peyghambarian, “Nonlinear Etalons and Optical Computing,” Proc. Soc. Photo-Opt. Instrum. Eng. 700, 64 (1986).
  11. S. D. Smith, “Optical Bistability, Photonic Logic and Optical Computation,” Appl. Opt. 25, 2550 (1986).
    [CrossRef]

1987 (6)

1986 (2)

H. M. Gibbs, N. Peyghambarian, “Nonlinear Etalons and Optical Computing,” Proc. Soc. Photo-Opt. Instrum. Eng. 700, 64 (1986).

S. D. Smith, “Optical Bistability, Photonic Logic and Optical Computation,” Appl. Opt. 25, 2550 (1986).
[CrossRef]

1978 (1)

Cathey, W. T.

Caulfield, H. J.

Dias, A. R.

Farhat, N. H.

N. H. Farhat, “Architectures for Optoelectronic Analogs of Self-organizing Neural Networks,” Opt. Lett. 12, 6 (1987).
[CrossRef]

Gibbs, H. M.

H. M. Gibbs, N. Peyghambarian, “Nonlinear Etalons and Optical Computing,” Proc. Soc. Photo-Opt. Instrum. Eng. 700, 64 (1986).

Goodman, J. W.

Guest, C.

B. Kosko, C. Guest, “Optical Bidirectional Associative Memories,” Proc. Soc. Photo-Opt. Instrum. Eng.758 (Jan.1987).

Handschy, M. A.

Johnson, K. M.

Kosko, B.

B. Kosko, C. Guest, “Optical Bidirectional Associative Memories,” Proc. Soc. Photo-Opt. Instrum. Eng.758 (Jan.1987).

B. Kosko, “Adaptive Bidirectional Associative Memories,” Appl. Opt. 26, 4947 (1987).
[CrossRef] [PubMed]

B. Kosko, “Competitive Adaptive Bidirectional Associative Memories,” in Proceedings, IEEE International Conference on Neural Networks (ICNN-1987), Vol. 2 (1987), pp. 759–766.

Pagano-Stauffer, L. A.

Peyghambarian, N.

H. M. Gibbs, N. Peyghambarian, “Nonlinear Etalons and Optical Computing,” Proc. Soc. Photo-Opt. Instrum. Eng. 700, 64 (1986).

Shamir, J.

Smith, S. D.

S. D. Smith, “Optical Bistability, Photonic Logic and Optical Computation,” Appl. Opt. 25, 2550 (1986).
[CrossRef]

Woody, L. M.

Appl. Opt. (4)

Opt. Lett. (3)

Proc. Soc. Photo-Opt. Instrum. Eng. (2)

B. Kosko, C. Guest, “Optical Bidirectional Associative Memories,” Proc. Soc. Photo-Opt. Instrum. Eng.758 (Jan.1987).

H. M. Gibbs, N. Peyghambarian, “Nonlinear Etalons and Optical Computing,” Proc. Soc. Photo-Opt. Instrum. Eng. 700, 64 (1986).

Other (2)

B. Kosko, Ed., Image Understanding, Proc. Soc. Photo-Opt. Instrum. Eng.758 (Jan.1987).

B. Kosko, “Competitive Adaptive Bidirectional Associative Memories,” in Proceedings, IEEE International Conference on Neural Networks (ICNN-1987), Vol. 2 (1987), pp. 759–766.

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Figures (2)

Fig. 1
Fig. 1

Flow diagram of a BAM.

Fig. 2
Fig. 2

Optical design for the BAM. A ray trace of one element shows the loop-back feature of this design. The element is processed and fed to a different location on the SLM.

Equations (10)

Equations on this page are rendered with MathJax. Learn more.

y i = Σ a i j x j ,
y i = + 1 if Σ ( a i j x j ) ( p ) > Σ ( a i j x j ) ( n ) - 1 if Σ ( a i j x j ) ( p ) < Σ ( a i j x j ) ( n ) .
Σ ( a i j x j ) = 1.
A = ( a 1 a 2 a n ) T ,
Σ a i j = M i .
A = ( c 1 a 1 c 2 a 2 c n a n ) T ,
c 1 Σ a 1 j = c 2 Σ a 2 j = c n Σ a n j = 1 ,
y = N L { A x }
y i = + 1 if y i = Σ ( a i j x j ) ( p ) > ½ - 1 if y i = Σ ( a i j x j ) ( p ) < ½ .
c n Σ a n j = α n ,

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