LEITE, N. M. N.; http://lattes.cnpq.br/4358099602140124; LEITE, Niago Moreira Nobre.
Resumo:
Convolution is a technique applied on mathematical signals in order to abstract new levels
of semantic comprehension about their characteristics. Such operation finds use in artificial
intelligence, the biomedical industry, electronic circuits design, and media processing. In
an increasingly automated global context, with a growing need for faster, more precise and
more efficient computational systems, the convenience of hardware-dedicated algorithm
implementations, as well as of different numerical representations in order to achieve set
requirements is not to be ignored.
During the development of this project, a unidimensional convolutional module was implemented
in hardware using fixed-point arithmetic, aiming to provide a platform that
would be able to accelerate such computations in algorithms that make its recurrent use,
such as digital signal processing schemes and artificial neural network structures. Implemented
models were simulated and synthesized, after which they were analysed under
both quantitative and qualitative lenses.