1 research outputs found
FPGA-Embedded Linearized Bregman Iterations Algorithm for Trend Break Detection
Detection of level shifts in a noisy signal, or trend break detection, is a
problem that appears in several research fields, from biophysics to optics and
economics. Although many algorithms have been developed to deal with such
problem, accurate and low-complexity trend break detection is still an active
topic of research. The linearized Bregman Iterations have been recently
presented as a low-complexity and computationally-efficient algorithm to tackle
this problem, with a formidable structure that could benefit immensely from
hardware implementation. In this work, a hardware architecture of the
Linearized Bregman Iterations algorithm is presented and tested on a Field
Programmable Gate Array (FPGA). The hardware is synthesized in different sized
FPGAs and the percentage of used hardware as well as the maximum frequency
enabled by the design indicate that an approximately 100 gain factor in
processing time, with respect to the software implementation, can be achieved.
This represents a tremendous advantage in using a dedicated unit for trend
break detection applications.Comment: 8 pages, 4 figure