5 papers
Mixed Potential Approach to Convergence of Nonlinear RLC Circuits with Memristors
Mauro Di Marco, Mauro Forti, Luca Pancioni +2
The paper considers a large class of nonlinear circuits, termed RLCM, containing all four basic circuit elements, i.e., resistors, inductors, capacitors and memristors. A companion…
Mixed potential for nonlinear RLC circuits with memristors
Mauro Di Marco, Mauro Forti, Luca Pancioni +2
In two seminal articles published in 1964, Brayton and Moser introduced the concept of a mixed potential as a fundamental theoretic tool to describe and analyze a class RLC of nonl…
Convergent Weight and Activation Dynamics in Memristor Neural Networks
Mauro Di Marco, Mauro Forti, Luca Pancioni +2
Convergence of dynamic feedback neural networks (NNs), as the Cohen-Grossberg, Hopfield and cellular NNs, has been for a long time a workhorse of NN theory. Indeed, convergence in…
A small-gain criterion for 2-contraction of large scale interconnected systems
David Angeli, Davide Martini, Giacomo Innocenti +1
Despite modular conditions to guarantee stability for large-scale systems have been widely studied, few methods are available to tackle the case of networks with multiple equilibri…
Embedding classic chaotic maps in simple discrete-time memristor circuits
Mauro Di Marco, Mauro Forti, Giacomo Innocenti +2
In the last few years the literature has witnessed a remarkable surge of interest for chaotic maps implemented by discrete-time (DT) memristor circuits. This paper investigates on…