抄録
This paper presents some properties of stable patterns that can be realized by a certain type of one-dimensional two-layer cellular neural networks (CNNs). We first introduce a notion of admissible local pattern (ALP) set. All the stable patterns of a CNN can be completely determined by the ALP set. We next show that all of 256 possible ALP sets can be realized by two-layer CNNs, while only 59 can be realized by single-layer CNNs. This means two-layer CNNs have a much higher potential for signal processing than single-layer CNNs.
| 本文言語 | English |
|---|---|
| ページ（範囲） | I385-I388 |
| ジャーナル | Midwest Symposium on Circuits and Systems |
| 巻 | 1 |
| 出版ステータス | Published - 12月 1 2004 |
| 外部発表 | はい |
| イベント | The 2004 47th Midwest Symposium on Circuits and Systems - Conference Proceedings - Hiroshima 継続期間: 7月 25 2004 → 7月 28 2004 |
ASJC Scopus subject areas
- 電子材料、光学材料、および磁性材料
- 電子工学および電気工学