Image Reconstruction by the Complex-Valued Neural Networks: Design by Using Generalized Projection Rule
نویسنده
چکیده
Storing gray-scale images with neural networks is a challenging problem and has received much attention in the past two decades. There are four main approaches for storing images with n pixels and K gray levels. The first approach is to encode the gray level of each pixel by R ( 2 log R K = ) binary neurons (Taketa & Goodman, 1986; Cernuschi-Frias, 1989; Lee, 1999). However, this method needs great numbers of neurons (nR) and interconnection weights ( 2 2 n R ). The second approach is based on neural networks with multivalued stable states (Si & Michel, 1991; Zurada, Cloete, & van der Poel, 1996). The activation function is a quantized nonlinearity with K plateaus ABSTrACT
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