Alexandre R. S. Romariz

Tunable vertical-cavity surface-emitting laser with feedback to implement a pulsed neural model. 1. Principles and experimental demonstration

An optoelectronic implementation of a modified FitzHugh-Nagumo neuron model is proposed, analyzed, and experimentally demonstrated. The setup uses linear optics and linear electronics for implementing an optical wavelength-domain nonlinearity. The system attains instability through a bifurcation mechanism present in a class of neuron models, a fact that is shown analytically. The implementation exhibits basic features of neural dynamics including threshold, production of short pulses (or spikes), and refractoriness.

Digital filter arbitrary magnitude and phase approximations - statistical analysis applied to a stochastic-based optimization approach

This paper presents a statistical analysis of stochastic-based optimization algorithms applied to a digital filter arbitrary magnitude and phase approximation design problem. Using an already developed rigorous statistical methodology, a completely randomized design is set up and best parameters values are estimated for the adaptive algorithms applied to a specific non-linear approximation problem. After finding the best parameter values, an additional completely randomized design is set up, comparing the performance of the adaptive algorithms with a quasi-Newton algorithm. Results for the statistical analysis are presented and the performance for different optimization algorithms with the best parameter values are analyzed.

Optimum Finite Impulse Response Digital Filter Design Using Computational Intelligence Based Optimization Algorithms

In this paper we use computational intelligence numerical optimization techniques to design optimum non-linear phase finite impulse response digital filters. The filter magnitude and group delay approximation will be presented as a classical approximation problem, where a non-linear function of several variables must be minimized. Results will be presented and compared with three different numerical optimization techniques developed, including Genetic algorithms, Simulated Annealing and Particle Swarm Optimization. Additionally, results are compared with a current used design technique, an unconstrained quasi-Newton algorithm.

A new biomechanical hand prosthesis controlled by surface electromyographic signals

This paper describes the development of a low-cost hand prosthesis for use in patients with an amputated hand due to congenital problems or to trauma wound, who possess a part or the forearm endowed with muscular activity. The paper covers the constructive aspects of both mechanical and electronic designs. The prototype is controlled by electromyographic signals measured at the remaining part of the injured limb of the patient. The EMG signals are measured at the surface of the skin, at a point that is close to a working muscle of the amputated arm. The prosthesis allows the patient to hold objects by means of a three finger clamp. The prosthesis presented an excellent performance in preliminary tests with an amputated patient. These tests showed that the prosthesis had a very good performance regarding force and speed.

Tunable vertical-cavity surface-emitting laser with feedback to implement a pulsed neural model. 2. High-frequency effects and optical coupling

The operation of an optoelectronic dynamic neural model implementation is extended to higher frequencies. A simplified model of thermal effects in vertical-cavity surface-emitting lasers correctly predicts the qualitative changes in the nonlinear mapping implementation with frequency. Experiments and simulations show the expected resonance properties of this model neuron, along with the possibility of other dynamic effects in addition to the ones observed in the original FitzHugh-Nagumo equations. Results of optical coupling between two similar pulsing artificial neurons are also presented.

Observation of negative differential resistance and hysteretic effect on buriti oil:polystyrene organic devices

The authors have observed hysteretic behavior and negative differential resistance in single-layer devices made from buriti oil mixed with polystyrene and sandwiched between poly(3,4-ethylenedioxythiophene)/poly(4-styrenesulfonate) and silver (Ag) electrodes. The hysteresis curve shows not only two different values of current but different behaviors as the increasing voltage curve shows negative differential resistance and the decreasing voltage curve does not. The fact that a simple fabrication technique yields reproducible conductance switching and hysteresis is relevant for the development of theories of organic electronic device behavior.

A proposal for human action classification based on motion analysis and artificial neural networks

This paper describes the development and application of a method for human action recognition from motion analysis in a sequence of images using an artificial neural network. The proposed method is based on two stages: Computer Vision and Computational Intelligence. The Computer Vision stage is a combination of two motion analysis techniques: Histogram of Oriented Optical Flow and Object Contour Analysis. For the Computational Intelligence stage we use a Self-Organizing Map (SOM) optimized through Learning Vector Quantization (LVQ). The approach is then applied for classification of human actions in many real situations. Testing against a database with different kinds of human actions, we show the usefulness and robustness of this method, comparing it to other proposals in the literature.

Análise de Filtros Espaciais em Sinais EMG de Superfície nas Condições do Máximo Volume de Contração

Nowadays the surface EMG measurement and its signal analysis have combined two important techniques in order to improve the signal resolution and better investigate single motor units: measurements configurations with smaller pick-up areas and application of the spatial filtering to electromyography. Smaller pick-up areas can be achieved through multielectrode arrays and multichannel recording, making possible the detection of correlated excitations at different sites of the muscle. Spatial filters combine the information of several electrodes to form one output signal channel. This work aims at evaluating the EMG signals measured from some subjects with a linear array of 16 electrodes and compare their resolution through the application of Bipolar, Longitudinal Double Diferentiating and Longitudinal Quadruple Diferentiating spatial filters.

Design of a hybrid digital-analog neural co-processor for signal processing

A hybrid architecture for neural coprocessing is presented. A fixed set of analog multipliers and capacitors (analog memory) emulates multilayer perceptrons through digitally-controlled multiplexing. Thus parallelism is partially preserved without direct analog implementation of the whole structure. Details of system VLSI implementation are given, along with simulation results and performance estimation.

Neural oscillator for gait command of a humanoid robot

In this article bio-inspired techniques are used for generating the gait of a biped robot. The concept of CPG, central pattern generator, which is a neural network capable of producing rhythm output, was used. It was modeled as coupled oscillators. With the purpose of verifying the operation of the oscillators, simulations were made. After that they were implemented for generating the gait for the robot. The output of the oscillators were used as the reference trajectory for the feet and the joint angles were obtained by inverse kinematics. We obtained good result in simulations for the humanoid robot, which showed a degree of tolerance to external perturbations.