High speed filtering using reconfigurable hardware
Carlos Perez-Vidal, Luis Gracia
JOURNAL OF PARALLEL AND DISTRIBUTED COMPUTING  (2009)
 ISSN:0743-7315  DOI:10.1016/j.jpdc.2009.06.004  - Vol. 69 pp. 896-904

Resumen:

This research develops a real-time implementation of computationally expensive prediction filters by means of task parallelization and task segmentation methodologies in an FPGA. There is a brief description of the prediction filter, then two types of implementations have been developed: PC-based sequential implementations using MATLAB and C++; and an FPGA-based parallelized implementation using VHDL. A comparative study between both types of implementations shows that the execution times measured on the FPGA are considerably lower, making this implementation valid for applications with real-time requirements. Experimental results are shown for a visual servoing task to illustrate the good performance of the proposed algorithms and implementations.