Neural networks and conditional association networks. common properties and differences

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Neural networks and conditional association networks. common properties and differences

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© The Institution of Electrical Engineers
Published

At first it is shown how large networks can be represented in an illustrative way. Then, the special aspects of neural networks are discussed. When conditional association arrays and semantic memories are plotted as networks surprising similiarities arise, but important characteristic differences can be seen too. The first experiments suggest that substantial progress in text processing may be achieved faster with conditional association networks than with neural networks.

Inspec keywords: parallel processing; content-addressable storage; neural nets

Other keywords: neural networks; conditional association networks; common properties; semantic memories; text processing

Subjects: Memory circuits; Systems theory applications in biology and medicine; Other digital storage; Artificial intelligence (theory)

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