Simulating Nonlinear Waves and Partial Differential Equations via CNN—Part II: Typical Examples
Research output: Contribution to journal › Research article › Contributed › peer-review
Contributors
Abstract
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.
Details
Original language | English |
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Pages (from-to) | 816-820 |
Number of pages | 5 |
Journal | IEEE Transactions on Circuits and Systems : 1, Fundamental Theory and Applications |
Volume | 42 |
Issue number | 10 |
Publication status | Published - Oct 1995 |
Peer-reviewed | Yes |
Externally published | Yes |
External IDs
ORCID | /0000-0001-7436-0103/work/142240247 |
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