Alejandro Diaz-Mendez

Implementation of a Linguistic Fuzzy Relational Neural Network for Detecting Pathologies by Infant Cry Recognition

In this paper we describe the implementation of a fuzzyrelational neural network model. In the model, the input features are represented by their respective fuzzy membership values to linguistic properties. The weights of the connections between input and output nodes are described in terms of their fuzzy relations. The output values during training are obtained with the max-min composition, and are given in terms of fuzzy class membership values. The learning algorithm used is a modified version of the back-propagation algorithm. The system is tested on an infant cry classification problem, in which the objective is to identify pathologies like deafness and asphyxia in recently born babies. The design and implementation of the classifier is presented, as well as results of some experiments.

A Fuzzy Relational Neural Network for Pattern Classification

In this paper we describe the implementation of a fuzzy relational neural network model. In the model, the input features are represented by fuzzy membership, the weights are described in terms of fuzzy relations. The output values are obtained with the max-min composition, and are given in terms of fuzzy class membership values. The learning algorithm is a modified version of back-propagation. The system is tested on an infant cry classification problem, in which the objective is to identify pathologies in recently born babies.

Interactive educational tool for compensators design in MATLAB® using frequency response analysis

This article presents an educational platform developed to support the teaching of compensators design in a basic control theory course. The application consists of a graphical user interface in MATLAB®, and further connection to the plant under study through the data acquisition toolbox, and a data acquisition card. The developed system allows the students to experiment with parameter changes in the controllers under study, such as gain, overshoot, settling time, and peak time, and visualize results obtained from simulated or real signals. The methodology is based on the frequency response analysis. Typical Bode, root locus, and unit step response plots are easily obtained for a system before and after compensation, in a dynamical way. A modular design allows the students to easily upgrade the application in order to include further methodologies. Results derived from its use in undergraduate and graduate courses are presented. MATLAB is a registered trademark of The MathWorks, Inc.© 2012 Wiley Periodicals, Inc. Comput Appl Eng Educ 22:699–707, 2014; View this article online at wileyonlinelibrary.com/journal/cae; DOI 10.1002/cae.21562

Design of a CMOS Compatible CFOA and its Application in Analog Filtering

This paper presents the design of a current-feedback operational amplifier (CFOA) which is suitable for implementation with standard CMOS integrated-circuit technology of 0.35 mum. The characteristics of the CFOA are derived by using biases of plusmn2.5 V and Ibias=20 muA. The usefulness of the CFOA is demonstrated by designing mixed-mode biquads which realize the low-pass, high-pass, band-pass, notch and all-pass filter functions. As a result, it is highlighted that the SPICE simulations of the biquad working in voltage-mode are in good agreement with the biquad working in current-mode