※一部利用できない機能があります
| 1.
図書 |
図書
|
Teuvo Kohonen
|
||||||
| 2.
論文 |
論文
|
Kobori, Hideki ; Ikeda, Kazushi ; Nakayama, Kenji
概要:
金沢大学理工研究域電子情報学系<br />A model of dynamic associative memories is proposed in this paper. The aim is to find all stored pa
…
tterns, and to distinguish the stored and the spurious patterns. Aihara used chaotic neurons and showed that his model has a nonperiodic associative dynamics. In his model, however, it is difficult to distinguish the stored patterns from the others, because the state of the network changes continually. We propose such a new model of neurons that each neuron changes its output to the other when the accumulation of its internal state exceeds a certain threshold. By computer experiments, we show that the state of the network stays at the stored pattern for a while and then travels around to another pattern, and so on. Furthermore, when the number of the stored patterns is small, the stored and the spurious patterns can be distinguished using interval of the network staying these patterns.
続きを見る
|
||||||
| 3.
論文 |
論文
|
Nakayama, Kenji ; Nishimura, Katsuaki
概要:
金沢大学理工研究域電子情報学系<br />An associative memory using fixed and variable hysteresis thresholds in learning and recalling proc
…
esses, respectively, has been proposed by authors. This model can achieve a large memory capacity and very low noise sensitivity. However, a relation between weight change Δ w and the hysteresis threshold ± T has not been well discussed. In this paper, a new learning algorithm is proposed, which is based on a delta rule. However, in order to stabilize the learning process, a method of using double hysteresis thresholds is proposed. Unit states are updated using ± T. The error, used for adjusting weights, is evaluated using ± (T+dT). This means 'over correction'. Stable and fast convergence can be obtained. Relations between η =dT/T and convergence rate and noise sensitivity are discussed, resulting the optimum selection for η. Furthermore, the order of presenting training data is optimized taking correlation, into account. In the recalling process, a threshold control method is further proposed in order to achieve fast recalling from noisy patterns.
続きを見る
|
||||||
| 4.
図書 |
図書
|
Teuvo Kohonen
|
