WANG Jin-gen, GONG Shen-guang, CHEN Shi-fu. Sufficient and Necessary Condition of the Extended Alternating Projection Neural Network Configured as a Content Addressable Memory[J]. Acta Electronica Sinica, 2004, 32(4): 596-600.
DOI:
WANG Jin-gen, GONG Shen-guang, CHEN Shi-fu. Sufficient and Necessary Condition of the Extended Alternating Projection Neural Network Configured as a Content Addressable Memory[J]. Acta Electronica Sinica, 2004, 32(4): 596-600.DOI:
Sufficient and Necessary Condition of the Extended Alternating Projection Neural Network Configured as a Content Addressable Memory
The paper extends the original Alternating Projection Neural Network(APNN) and proposes an Extended Alternating Projection Neural Network (EAPNN) which functions in the field of complex numbers.An improved weight-learning approach
which permits linear dependence of complex patterns
has been presented.A general mathematical expression of the EAPNN steady-state solution has been obtained.From the general mathematical expression we have derived the sufficient and necessary condition of the EAPNN configured as a content addressable memory.In addition
simulation experiments have been designed to verify the theoretical analyses in the paper.Finally it is pointed out that the EAPNN has been applied to signal processing such as band-limited signal extrapolation