𝔖 Bobbio Scriptorium
✦   LIBER   ✦

Statistical physics on cellular neural network computers

✍ Scribed by M. Ercsey-Ravasz; T. Roska; Z. Néda

Publisher
Elsevier Science
Year
2008
Tongue
English
Weight
495 KB
Volume
237
Category
Article
ISSN
0167-2789

No coin nor oath required. For personal study only.

📜 SIMILAR VOLUMES

Parallelization of cellular neural netwo
Parallelization of cellular neural networks on GPU
✍ Tze-Yui Ho; Ping-Man Lam; Chi-Sing Leung 📂 Article 📅 2008 🏛 Elsevier Science 🌐 English ⚖ 983 KB

Recently, cellular neural networks (CNNs) have been demonstrated to be a highly effective paradigm applicable in a wide range of areas. Typically, CNNs can be implemented using VLSI circuits, but this would unavoidably require additional hardware. On the other hand, we can also implement CNNs purely

On stability of delayed cellular neural
On stability of delayed cellular neural networks
✍ Jinde Cao 📂 Article 📅 1999 🏛 Elsevier Science 🌐 English ⚖ 73 KB

## Ž . A set of sufficient criteria are found ensuring the global asymptotic stability of delayed cellular neural networks DCNN with more general output functions by introducing ingeniously real parameters a Ž . s 1,a q b s 1,h q z s 1,h q z s 1 j s 1,2, PPP ,n , constructing suitable Lyapunov fu

Cellular neural networks as a general ma
Cellular neural networks as a general massively parallel computational paradigm
✍ Destri, Giulio; Marenzoni, Paolo 📂 Article 📅 1996 🏛 John Wiley and Sons 🌐 English ⚖ 896 KB

In this paper is presented the use of the discrete-time cellular neural network (DTCNN) paradigm to develop algorithms devised for general-purpose massively parallel processing (MPP) systems. This paradigm is defined in discrete N-dimensional spaces (lattices) and is characterized by the locality of