Mohcin Mekhfioui, A. Satif, Omar Mouhib, R. Elgouri, A. Hadjoudja, L. Hlou
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引用次数: 2
摘要
盲源分离(BSS)是指在不了解源信号或对源信号知之甚少的情况下从混合数据中提取源信号。它被用于许多研究领域,如军事、医疗和工业。在将BSS应用于实际系统必须克服的许多挑战中,实现限制是最困难的。软件实现需要大量的开销才能使它们适用于实时系统,并且具有比硬件实现更低的最大操作速度。当需要速度时,算法应该在专门的硬件上实现,例如现场可编程门阵列(FPGA),它允许用户利用并行计算能力。本文介绍了在FPGA上实现实时DSP应用的方法,以及利用MATLAB Simulink和Xilinx System Generator (XSG)对二阶盲识别(SOBI)算法进行软硬件协同仿真的概念。在FPGA ZYBO Z7 Zynq-7020上实现了高效架构的性能。
Hardware Implementation of Blind Source Separation Algorithm Using ZYBO Z7& Xilinx System Generator
Blind Source Separation (BSS) is termed as the extraction of source signals from mixed data without or with little knowledge about the source signals. It is used in many fields of research such as military, medical and industry. Among the many challenges that must be overcome to apply BSS to a real system, implementation restrictions are the most difficult. Software implementations require a significant amount of overhead to make them applicable to real-time systems and have a lower maximum speed of operation than hardware implementations. When speed is desired, the algorithm should be implemented on specialized hardware such as a Field Programmable Gate Array(FPGA) which allows the user to take advantage of parallel computational abilities. This paper describes the methodology for implementing real-time DSP applications on FPGA and the concept of hardware software cosimulation of the Second Order Blind Identification (SOBI) algorithm using MATLAB Simulink and Xilinx System Generator (XSG). Performances of efficient architectures are implemented on FPGA ZYBO Z7 Zynq-7020.