Producción Científica Profesorado

2011

Miranda-Romagnoli, P., Hernández-Romero, N., & Seck-Tuoh Mora, J. C. (2011) A Neuro Fuzzy Solution in the Design of Anlog Circuits. IEICE TRANS. FUNDAMENTALS, E-94A (1), 434-439.

**Abstract**

A neuro fuzzy method to design analog circuits is explained, where the universe of discourse of the fuzzy system is adjusted by means of a self-organized artificial neural network. As an example of this approach, an op-amp is optimized in order to hold a predetermined aim; where the unity gain bandwidth is an objective of design, and the restrictions of open-loop gain and margin phase are treated as objectives too. Firstly, the experience of the behavior of the circuit is obtained, hence an inference system is constructed and a neural network is applied to achieve a faster convergence into a desired solution. This approach is characterized by having a simple implementation, a very natural understanding and a better performance than static methods of fuzzy optimization.

Unconventional invertible behaviors in reversible one-dimensional cellular automata.

Modeling a Nonlinear Liquid Level System by Cellular Neural Networks

Complex Dynamics Emerging in Rule 30 with Majority Memory

How to Make Dull Cellular Automata Complex by Adding Memory: Rule 126 Case Study

Pair Diagram and Cyclic Properties Characterizing the Inverse of Reversible Automata

Elementary cellular automaton Rule 110 explained as a block substitution system

Reproducing the Cyclic Tag System Developed by Matthew Cook with Rule 110 Using the Phases f(i-)1.