The design algorithm of an associative memory neural network

A design algorithm of an associative memory neural network is proposed. The benefit of this design algorithm is to make the designed associative memory model can implement the hoped situation. On the one hand, the designed model has realized the nonlinear association of infinite value pattern from n dimension space to m dimension space. The result has improved the ones of some old associative memory neural network. On the other hand, the memory samples are in the centers of the fault-tolerant. In average significance the radius of the memory sample fault-tolerant field is maximum.

Performance improvement by charge trapping of doping fluorescent dyes in organic memory devices

We studied the memory effect in the devices consisting of dye-doped N, N'-di(naphthalene-1-yl)-N, N'-diphenyl-benzidine sandwiched between indium-tin oxide and Ag electrodes. It was found that the on/off current ratio was greatly improved by the doped fluorescent dyes compared with nondoping devices. A mechanism of charge trapping was demonstrated to explain the improvement of the memory effect. For the off state, the conduction process is dominated by the trapping current, which is a characteristic of the space-charge limited current, whereas the on state is dominated by the detrapping current, and interpreted by Poole-Frenkel emission.