Optimization methods for pattern recognition

Efficient signal processing is made possible by using hybrid electro-optical systems which can be trained to perform a specific task. Various architectures and procedures are implemented for optimization of pattern recognition and other signal processing systems.

[1]  H J Caulfield,et al.  Improved discrimination in optical character recognition. , 1969, Applied optics.

[2]  Uri Mahlab,et al.  Adaptive learning with joint transform correlators , 1990 .

[3]  D W Sweeney,et al.  Iterative technique for the synthesis of distortion-invariant optical correlation filters. , 1987, Optics letters.

[4]  J Shamir,et al.  Iterative generation of holograms on spatial light modulators. , 1990, Optics letters.

[5]  B. V. K. Vijaya Kumar,et al.  Review Of Synthetic Discriminant Function Algorithms , 1989, Other Conferences.

[6]  Richard D. Juday,et al.  Relaxation Method Of Compensation In An Optical Correlator , 1987 .

[7]  H Bartelt,et al.  Improving binary phase correlation filters using iterative techniques. , 1985, Applied optics.

[8]  D Mendlovic,et al.  Complex reference-invariant joint-transform correlator. , 1990, Optics letters.

[9]  D. Casasent,et al.  Minimum average correlation energy filters. , 1987, Applied optics.

[10]  B. Kumar,et al.  Generalized synthetic discriminant functions , 1988 .

[11]  Uri Mahlab,et al.  Error probability in optical pattern recognition , 1990 .

[12]  Y Fainman,et al.  Optical implementation of an iterative algorithm formatrix inversion. , 1987, Applied optics.

[13]  J D Downie,et al.  Experimental verification of modified synthetic discriminant function filters for rotation invariance. , 1990, Applied optics.

[14]  J. Goodman,et al.  A technique for optically convolving two functions. , 1966, Applied optics.

[15]  A. B. Vander Lugt,et al.  Signal detection by complex spatial filtering , 1964, IEEE Trans. Inf. Theory.

[16]  O. Bryngdahl,et al.  I Digital Holography – Computer-Generated Holograms , 1990 .

[17]  A W Lohmann,et al.  Optical character recognition based on nonredundant correlation measurements. , 1979, Applied optics.

[18]  C C Guest,et al.  Simulated annealing algorithm for binary phase only filters in pattern classification. , 1990, Applied optics.

[19]  Tuvia Kotzer,et al.  Optical implementation of phase extraction pattern recognition , 1991 .

[20]  Ravindra A. Athale Optical Matrix Processors , 1986, Other Conferences.

[21]  Wilburn E. Reddick,et al.  Automated spatial filter optimization using frequency-domain simulated annealing , 1992 .

[22]  J Shamir,et al.  Genetic algorithm for optical pattern recognition. , 1991, Optics letters.

[23]  D Casasent,et al.  Unified synthetic discriminant function computational formulation. , 1984, Applied optics.

[24]  B. Kumar,et al.  Performance measures for correlation filters. , 1990, Applied optics.

[25]  David Mendlovic,et al.  Real-time optical generation of circular or Mellin radial-harmonic filters , 1990 .

[26]  J Shamir,et al.  Application of the projection-onto-constraint-sets algorithm for optical pattern recognition. , 1991, Optics letters.

[27]  J Shamir,et al.  Entropy optimized filter for pattern recognition. , 1990, Applied optics.

[28]  D A Jared,et al.  Inclusion of filter modulation in synthetic-discriminant-function construction. , 1989, Applied optics.

[29]  R. Kallman Construction of low noise optical correlation filters. , 1986, Applied optics.

[30]  J. Allebach,et al.  Synthesis of digital holograms by direct binary search. , 1987, Applied optics.