A Hardware-Oriented Echo State Network for FPGA Implementation

被引:0
作者
Honda, Kentaro [1 ]
Tamukoh, Hakaru [1 ]
机构
[1] Kyushu Inst Technol, Grad Sch Life Sci & Syst Engn, Wakamatsu Ku, 2-4 Hibikino, Kitakyushu, Fukuoka 8080196, Japan
来源
PROCEEDINGS OF THE 2020 INTERNATIONAL CONFERENCE ON ARTIFICIAL LIFE AND ROBOTICS (ICAROB2020) | 2020年
关键词
Reservoir Computing; Echo State Network; Field Programmable Gate Array;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
This paper proposes implementation of an echo state network (ESN) to field programmable gate array FPGA). The proposed method is able to reduce hardware resources by using fixed-point operation, quantization of weights, which includes accumulate operations and efficient dataflow modules. The performance of the designed circuit is verified via experiments including prediction of sine and cosine waves. Experimental result shows that the proposed circuit supports to 200[MHz] of operation frequency and facilitates faster computing of the ESN algorithm compared with a central processing unit.
引用
收藏
页码:187 / 190
页数:4
相关论文
共 5 条
[1]   A fast learning algorithm for deep belief nets [J].
Hinton, Geoffrey E. ;
Osindero, Simon ;
Teh, Yee-Whye .
NEURAL COMPUTATION, 2006, 18 (07) :1527-1554
[2]  
Jaeger H., 2001, GERMAN NAT RES CNTR, V148, P13
[3]  
Majima T, 2017, 2017 FOURTH ASIAN CONFERENCE ON DEFENCE TECHNOLOGY - JAPAN (ACDT), P58
[4]   BACKPROPAGATION THROUGH TIME - WHAT IT DOES AND HOW TO DO IT [J].
WERBOS, PJ .
PROCEEDINGS OF THE IEEE, 1990, 78 (10) :1550-1560
[5]   Re-visiting the echo state property [J].
Yildiz, Izzet B. ;
Jaeger, Herbert ;
Kiebel, Stefan J. .
NEURAL NETWORKS, 2012, 35 :1-9