Reprints

[Dr. S. Kak]

Reprints of the following article are now available:

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Ciruits, Systems, & Signal Processing, vol. 12, 1993, pp. 263-278
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Feedback Neural Networks: New Characteristics and a Generalization

Subhash C. Kak

Department of Electrical and Computer Engineering
Louisiana State University, Baton Rouge, LA 70803, USA

ABSTRACT

New characteristics of feedback neural networks are studied.
We discuss in detail the question of updating of neurons
given incomplete information about the state of the neural network.
We show how the mechanism of self-indexing 
[Self-indexing of neural
memories, Physics Letters A, Vol. 143, 293-296, 1990.]
for such updating provides better results than assigning 'don't know'
values to the missing parts of the state vector.
Issues related to the choice of the neural model
for a feedback network are also considered.
Properties of a new complex valued neuron model that generalizes
McCulloch-Pitts neurons are examined.
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Note: This issue of the journal is devoted exclusively to
articles on neural networks.