9 March 1999 Feedback neural network for pattern recognition
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In the present paper, a new synthesis approach is developed for associate memories based on a modified relaxation algorithm. The design problem, of feedback neural networks for associative memories is formulated as a set of linear inequalities such that the use of pseudo relaxation method is evident. The pseudo relaxation training in the synthesis algorithms is guaranteed to converge for the design of neural networks without any constraints on the connection matrix. To demonstrate the applicability of the present result and to compare the present synthesis approach with existing design methods, a pattern recognition example is considered.
© (1999) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Ismail Salih, Ismail Salih, Stanley H. Smith, Stanley H. Smith, "Feedback neural network for pattern recognition", Proc. SPIE 3647, Applications of Artificial Neural Networks in Image Processing IV, (9 March 1999); doi: 10.1117/12.341120; https://doi.org/10.1117/12.341120


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