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SIMULATING NONLINEAR-WAVES AND PARTIAL-DIFFERENTIAL EQUATIONS VIA CNN .2. TYPICAL EXAMPLES

被引：58
作者：
KOZEK, T
CHUA, LO
ROSKA, T
WOLF, D
TETZLAFF, R
PUFFER, F
LOTZ, K
机构：
[1] UNIV CALIF BERKELEY,ELECTR RES LAB,BERKELEY,CA 94720
[2] UNIV CALIF BERKELEY,DEPT ELECT ENGN & COMP SCI,BERKELEY,CA 94720
[3] UNIV FRANKFURT,INST PHYS APPL,W-6000 FRANKFURT,GERMANY
来源：
IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS I-FUNDAMENTAL THEORY AND APPLICATIONS | 1995年 / 42卷 / 10期
基金：
匈牙利科学研究基金会; 美国国家科学基金会;
关键词：
D O I：
10.1109/81.473591
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
Application of cellular neural network (CNN) paradigm of locally connected analog array-computing structures is considered for solving partial differential equations (PDE's) and systems of ordinary differential equations (ODE). Three examples are presented: a chain of particles with nonlinear interactions, solitons in a nonlinear Klein-Gordon equation, and an application of a reaction-diffusion CNN for fingerprint enhancement.
引用
收藏
页码：816 / 820
页数：5
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