Training a Network with Ternary Weights Using the CHIR Algorithm

S. Abramson, E. Marom

Research output: Contribution to journalArticlepeer-review


A modification of the binary weight CHIR algorithm is presented, whereby a zero state is added to the possible binary weight states. This method allows obtaining solutions with reduced connectivity, by offering disconnections in addition to the excitatory and inhibitory connections. The algorithm was examined via extensive computer simulations for the restricted cases of parity, symmetry, and teacher problems, which show similar convergence rates to those presented for the binary CHIR2 algorithm, however, with reduced connectivity. Moreover, this method expands the set of problems solvable via the binary weight network configuration with no additional parameter requirements.

Original languageEnglish
Pages (from-to)997-1000
Number of pages4
JournalIEEE Transactions on Neural Networks
Issue number6
StatePublished - Nov 1993


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