Title :
Simulating nonlinear waves and partial differential equations via CNN. II. Typical examples
Author :
Kozek, Tibor ; Chua, Leon O. ; Roska, Tamas ; Wolf, Dietrich ; Tetzlaff, Ronald ; Puffer, Frank ; Lotz, Karoly
Author_Institution :
Comput. & Autom. Inst., Hungarian Acad. of Sci., Budapest, Hungary
fDate :
10/1/1995 12:00:00 AM
Abstract :
For part I see ibid., vol.42, no.10, pp.807-15 (1995). 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
Keywords :
cellular neural nets; diffusion; fingerprint identification; nonlinear differential equations; partial differential equations; solitons; wave equations; CNN; cellular neural network; fingerprint enhancement; locally connected analog array-computing structures; nonlinear Klein-Gordon equation; nonlinear waves; ordinary differential equations; partial differential equations; particle chain; reaction-diffusion system; simulation; solitons; Automation; Cellular neural networks; Differential equations; Fingerprint recognition; Laboratories; Nonlinear equations; Partial differential equations; Solitons; Turing machines; Very large scale integration;
Journal_Title :
Circuits and Systems I: Fundamental Theory and Applications, IEEE Transactions on
