David Báez-López

Power Lab: A tool to learn electrical machines and power electronics

We describe a tool used in the teaching of power electronics that allows users to see how DC motors and AC/DC converters work without complicated circuits or arrangements. It also provides a user‐friendly interface owing to its development under the Windows environment. The tool described is called Power Lab. The goal of the tool is to introduce students to the DC motor control area, showing some functions for the motor such as full voltage starting, reduced starting voltage, stopping, reverse rotation, and speed regulation in a closed loop. Through the achievement of the motors function, students can also observe the performance of an AC/DC power converter with phase‐angle control and on/off control. Power Lab has the capability to work either as a stand‐alone tool or connected to a power stage. Several examples describe the applications of Power Lab.

Package for filter design based on MATLAB

Electric filters have a relevant importance in electronic systems because they are present in almost any electronic system. For example, communication systems, as many other electric systems, make intensive use of filtering to separate unwanted noise from the desired signal. Unfortunately, filter design is an intensive computational task requiring a significant amount of numerical calculations to obtain either the parameters of a filter transfer function or the element values for a filter circuit realization. This paper describes a software package whose purpose is to provide a tool to be used as a teaching aid in analog and digital filter design courses. The feature of this package is that it uses MATLAB [ 2 ] for the numerical computations. The main advantage of the filter design software package described in this paper is that makes uses of one of the MATLAB toolboxes, the signals toolbox (which is used for analog and digital filter design), but used with an interface that makes possible even to the novice user to readily design filters, either analog or digital, without any previous knowledge of MATLAB or the signals toolbox.

An FPGA-based architecture for linear and morphological image filtering

Field Programmable Gate Array (FPGA) technology has become a viable target for the implementation of real time algorithms suited to video image processing applications. The unique architecture of the FPGA has allowed the technology to be used in many applications encompassing all aspects of video image processing. Among those algorithms, linear filtering based on a 2D convolution, and non-linear 2D morphological filters, represent a basic set of image operations for a number of applications. In this work, an implementation of linear and morphological image filtering using a FPGA NexysII, Xilinx, Spartan 3E, with educational purposes, is presented. The system is connected to a USB port of a personal computer, which in that way form a powerful and low-cost design station. The FPGA-based system is accessed through a Matlab graphical user interface, which handles the communication setup. A comparison between results obtained from MATLAB simulations and the described FPGA-based implementation is presented.

Comparison of lossless compression techniques

Data compression deals with representing information in a succinct way. In view that the major lossless or error-free compression methods like Huffman, arithmetic and Lempel-Ziv coding do not achieve great compression ratios, it is necessary to preprocess the images in order to reduce the amount of correlation among neighboring pixels, thereby the compression ratio is improved. These preprocessing methods could achieve reduction of image entropy in the spatial domain, or in the spatial frequency domain. The performance of some lossless compression techniques in combination with preprocessing methods is examined.<<ETX>>

A package for filter design based on MATLAB

Electric filters have a relevant importance in electronic systems because they are present in almost any electronic system. For example, communication systems, as many other electric systems, make intensive use of filtering to separate unwanted noise from the desired signal. Unfortunately, filter design is an intensive computational task requiring a significant amount of numerical calculations to obtain either the parameters of a filter transfer function or the element values for a filter circuit realization. This paper describes a software package whose purpose is to provide a tool to be used as a teaching aid in analog and digital filter design courses. The feature of this package is that it uses MATLAB for the numerical computations. The main advantage of the filter design software package described in this paper is that it makes uses of one of the MATLAB toolboxes, the signals toolbox (which is used for analog and digital filter design), but used with an interface that makes it possible even to the novice user to readily design filters, either analog or digital, without any previous knowledge of MATLAB or the signals toolbox.

Focusing and defocusing vision system (SIVEDI)

Machine vision has been made easier by the development of computer systems capable of processing information at high speeds and by inexpensive camera-computer systems. A camera-computer system called SIVEDI was developed based in the shape from focusing technique (SFF) as proposed by Jenn (1997) and a shape from defocusing technique (SFD) developed in this research. The SIVEDI system has as entries the images captured by the camera, the number of steps of the focus mechanism, and the user specifications. The focus mechanism used is the internal one of the camera. To control it an interface computer-camera was designed and developed. An equation is introduced to obtain the measure of relative defocus among many images. A 3D image is produced as the result of the system. SIVEDI consist of a number of modules, each one implementing a step in the system model. The modules are independent of each other and could be easily modified to improve the system. As SIVEDI was developed in the MatLab environment, it can be used in any computer with this software on it. These characteristics offer the user access to the intermediate results and to control the system internal parameters. Results show that the 3D image reconstruction has an acceptable quality.

A voice recognition system for speech impaired people

We show how MATLAB can be used to realize voice recognition for people with cerebral paralysis. The first part of this paper is about what cerebral paralysis is, and its consequences on the way people with this illness talk. We then mention the mathematical background needed to realize this project. We explain the first stage of the system in which some phonemes are recognized. Next, we describe the functioning of the second stage of the project in which words are recognized. Finally, we give some results and we discuss them.

Satellite-Indoor Mobile Communications Path Propagation Losses

A software that calculates satellite indoor loss path for three different systems of mobile satellite communications is presented. The systems are GLOBALSTAR , IRIDIUM and a third option for a GENERAL system in which the user have the possibility of change some parameters of the calculations. The user can choose from 5 different indoor propagation models. The software was developed using Visual Basic.

Multi-modal medical image registration based on non-rigid transformations and feature point extraction by using wavelets

In order to correctly match two sets of images from different modalities, our method applies a non-rigid transformation to one set to get as close as possible to the other. This requires the estimation of the optimal similarity transformation between the two set of images. Estimation of the non-rigid deformation between the two sets of images is referred to as the deformation estimation between the pair of three-dimensional object extracted from both sets. We present a new methodology for image registration by first extracting objects from the set of images by reconstructing the object surfaces where this extraction supports semi-automatic segmentation of sets of 3-D medical images and then finding the best similarity transformation based on matching of two sets of surface points, but also incorporates the matching of two sets of feature points, and we have shown that deformation estimates based on simultaneous matching of surfaces and features are more accurate than those based on surface matching alone. This is especially true when the deformation involves physically realistic cases, such as those in human organs. Our technique uses free-form deformation models and applies the wavelet transform to extract feature points in the 3-D space. Feature point extraction also provides a means to compute the error in our estimates. We have applied our method to register sequences of MRI images to histology images of the carotid artery.

DSP lab course experiments based on the Motorola DSP56K processor

This paper describes a set of real time experiments for a digital signal processing undergraduate course. These experiments are based upon the Motorola 56K DSP processor. The main purpose of the experiments described is to allow students to appreciate the potential of DSP processors to implement digital filters. The experiments described range from function generation to IIR and FIR filter design. The code is available to interested instructors as shareware files. Data for the digital filters designed and implemented in these experiments is obtained from the MATLAB Signals Toolbox and from other design packages available.