Enhanced emulated digital CNN-UM (CASTLE) arithmetic cores

被引：0
|
作者：
Hidviégi, T
Keresztes, P
Szolgay, P
机构：
[1] Hungarian Acad Sci, Inst Comp & Automat, Analog & Neural Comp Syst Lab, H-1502 Budapest, Hungary
[2] Istvan Szechenyi Univ, H-9026 Gyor, Hungary
[3] Univ Veszprem, Image Proc & Neurocomp Dept, Veszprem, Hungary
来源：
JOURNAL OF CIRCUITS SYSTEMS AND COMPUTERS | 2003年 / 12卷 / 06期
关键词：
cellular nonlinear/ neural networks (CNN); emulated digital architecture; optimized arithmetic core; CNN Universal Machine;
D O I：
10.1142/S0218126603001136
中图分类号：
TP3 [计算技术、计算机技术];
学科分类号：
0812 ;
摘要：
An emulated digital CNN-UM (CASTLE) architecture was published few years ago.(1) Different emulated digital CNN-UM architectures are analyzed in the paper. These new modified architectures are optimized according to the silicon area, operating speed or dissipated power. A reconfigurable arithmetic core will also be shown in the paper, by which solution of the neighborhood size can be changed. An advanced CASTLE with pipe-lining is presented. The operation frequency is increased by using this solution in approximately 10 times.
引用
收藏
页码：711 / 738
页数：28
相关论文
共 50 条
  • [21] An Emulated Digital CNN Implementation
    Péter Keresztes
    Ákos Zarándy
    Tamás Roska
    Péter Szolgay
    Tamás Bezák
    Timót Hidvégi
    Péter Jónás
    Attila Katona
    Journal of VLSI signal processing systems for signal, image and video technology, 1999, 23 : 291 - 303
  • [22] An emulated digital CNN implementation
    Keresztes, P
    Zarándy, A
    Roska, T
    Szolgay, P
    Bezák, T
    Hidvégi, T
    Jónás, P
    Katona, A
    JOURNAL OF VLSI SIGNAL PROCESSING SYSTEMS FOR SIGNAL IMAGE AND VIDEO TECHNOLOGY, 1999, 23 (2-3): : 291 - 303
  • [23] Emulated digital CNN implementation
    Keresztes, Péter
    Zarándy, Ákos
    Roska, Tamás
    Szolgay, Péter
    Bezák, Tamás
    Hidvégi, Timót
    Jónás, Péter
    Katona, Attila
    Journal of VLSI Signal Processing Systems for Signal, Image, and Video Technology, 1999, 23 (02): : 291 - 303
  • [24] Statistical error modeling of CNN-UM architectures:: The grayscale case
    Földesy, P
    CELLULAR NEURAL NETWORKS AND THEIR APPLICATIONS, 2002, : 475 - 482
  • [25] An Alternative Proof of the Universality of the CNN-UM and its Practical Applications
    Egidio Pazienza, Giovanni
    Vilasis-Cardona, Xavier
    Poli, Riccardo
    2008 11TH INTERNATIONAL WORKSHOP ON CELLULAR NEURAL NETWORKS AND THEIR APPLICATIONS, 2008, : 34 - +
  • [26] Inverse elastic wave propagation modeling on CNN-UM architecture
    Sonkoly, P
    Kocsárdi, S
    Kozma, P
    Szolgay, P
    Proceedings of the 2005 European Conference on Circuit Theory and Design, Vol 1, 2005, : 79 - 82
  • [27] Artificial immune systems based novelty detection with CNN-UM
    Cserey, Gyoergy
    Roska, Tamas
    2007 IEEE SYMPOSIUM ON FOUNDATIONS OF COMPUTATIONAL INTELLIGENCE, VOLS 1 AND 2, 2007, : 156 - +
  • [28] QCIF resolution binary I/O CNN-UM chip
    Paasio, Ari
    Kananen, Asko
    Halonen, Kari
    Porra, Veikko
    Journal of VLSI Signal Processing Systems for Signal, Image, and Video Technology, 1999, 23 (02): : 281 - 290
  • [29] A QCIF Resolution Binary I/O CNN-UM Chip
    Ari Paasio
    Asko Kananen
    Kari Halonen
    Veikko Porra
    Journal of VLSI signal processing systems for signal, image and video technology, 1999, 23 : 281 - 290
  • [30] Statistical error modeling of CNN-UM architectures:: The binary case
    Földesy, P
    CELLULAR NEURAL NETWORKS AND THEIR APPLICATIONS, 2002, : 467 - 474
12345