基于FPGA的线性化Bregman迭代趋势突变检测算法
FPGA-Embedded Linearized Bregman Iterations Algorithm for Trend Break Detection
摘要：
检测噪声信号中的电平变化，或趋势突变检测，是从生物物理学到光学和经济学的几个研究领域中出现的问题。虽然已经有很多算法被开发出来来处理这样的问题，但准确和低复杂度的趋势突变检测仍然是一个活跃的研究课题。线性化Bregman迭代最近被提出作为一种低复杂度和计算效率高的算法来解决这个问题，具有强大的结构，可以极大地受益于硬件实现。在这项工作中，线性化Bregman迭代算法的硬件架构，并在现场可编程门阵列（FPGA）上进行测试。硬件在不同尺寸的FPGA中进行合成，所用硬件的百分比以及设计启用的最大频率表明，相对于软件实现，可以实现处理时间的约100增益因子。这代表了使用专用单元进行趋势突变检测应用的巨大优势。
英文摘要：
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.
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