Digital filter implementation over FPGA platform with LINUX OS

AbstractThe embedded processors on FPGA's are a good tool to specific propose works. In this work we present how the FPGA is used to apply a Sobel filter to a set of images, also the step needed to set-up the entire system is described. An embedded processor, with a Linux distribution implemented is used to run a special compilation of C filter program, the filter is compared with the results obtained with a PC running the same filter, in the embedded system all the process runs in the FPGA and the exit file can be accessed by ftp or http server embedded into the Linux system

Proposal of a Planar Directional UWB Antenna for Any Desired Operational Bandwidth

A novel planar directional UWB antenna is proposed. The antenna design evolves from an oblique elliptic cone antenna by applying the planar-solid correspondence to two axes. Through a simple equation, this antenna can be designed, to operate at a specific lower cutoff frequency with a bandwidth larger than 10 GHz for a reflection coefficient magnitude lower than −10 dB. This characteristic provides the antenna with a good versatility. The directional radiation pattern has an average gain of 6 dBi

Generalized Regression Neural Networks with Application in Neutron Spectrometry

The aim of this research was to apply a generalized regression neural network (GRNN) to predict neutron spectrum using the rates count coming from a Bonner spheres system as the only piece of information. In the training and testing stages, a data set of 251 different types of neutron spectra, taken from the International Atomic Energy Agency compilation, were used. Fifty-one predicted spectra were analyzed at testing stage. Training and testing of GRNN were carried out in the MATLAB environment by means of a scientific and technological tool designed based on GRNN technology, which is capable of solving the neutron spectrometry problem with high performance and generalization capability. This computational tool automates the pre-processing of information, the training and testing stages, the statistical analysis, and the post-processing of the information. In this work, the performance of feed-forward backpropagation neural networks (FFBPNN) and GRNN was compared in the solution of the neutron spectrometry problem. From the results obtained, it can be observed that despite very similar results, GRNN performs better than FFBPNN because the former could be used as an alternative procedure in neutron spectrum unfolding methodologies with high performance and accuracy

Theoretical Model to Determine the Blocking Probability for SDMA Systems.

NoAntenna array technology has attracted the attention of the research community as a means to increase system capacity and improve the signal reception. Space division multiple access (SDMA) is a multi-access scheme based on the use of antenna arrays to separate users by exploiting their positions in space. Several works have been carried out to examine the improvement in the system capacity provided by SDMA. A theoretical model to determine the blocking probability for SDMA is derived. A closed-form linear system of equations is obtained whose numerical solution gives the blocking probability. The formulation is employed to assess the capacity gain improvement of a single-cell system under specific conditions. It is found from the results that SDMA is not efficient for low traffic loads, whereas it is so for high traffic

A New Positioning Algorithm Robust to Measured Distances Errors for Non-Overdetermined Systems

International audienc

Performance Comparison of Positioning Algorithms for UAV Navigation Purposes based on Estimated Distances

International audienc