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A comparative analysis of multiplier-less 1-level discrete wavelet transform implementations on FPGAs

机译:乘法器较少的1级离散小波变换实现对FPGA的比较分析

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Using discrete wavelet transform (DWT) in highspeed signal processing applications imposes a high degree of care to hardware resource availability, latency and power consumption. In this paper, we investigate the design and implementation aspects of 1-level DWT by employing a finite impulse response (FIR) filter on FPGA platform. FPGAs come with a limited number of multipliers, which restricts the size and number of DWT levels. As a result, a multiplication-free architecture becomes a necessity for implementing large DWT. Our goal is to estimate the performance requirements and hardware resources for two key multiplication-free architectures, namely, distributed arithmetic algorithm (DAA) and residue number system (RNS), allowing for selection of the proper algorithm and implementation of DAA and RNS-based DWT. The design has been implemented and synthesized in Xilinx Virtex-6 ML605 FPGA, taking advantage of Virtex-6's embedded block RAMs (BRAMs). The results show that the DAA-based approach is appropriate and feasible for a small number of filter taps, while the RNS-based approach would be more appropriate for more than 10 filter taps.
机译:使用高速信号处理应用中的离散小波变换(DWT)对硬件资源可用性,延迟和功耗施加了高度的注意。在本文中,我们通过在FPGA平台上采用有限脉冲响应(FIR)滤波器来研究1级DWT的设计和实现方面。 FPGA具有有限数量的乘数,这限制了DWT级别的大小和数量。结果,乘法架构成为实现大DWT的必要性。我们的目标是估算两个关键乘法架构的性能要求和硬件资源,即分布式算术算法(DAA)和残差编号系统(RNS),允许选择正确的算法和基于RNS的实现DWT。该设计已在Xilinx Virtex-6 ML605 FPGA中实现和合成,利用Virtex-6的嵌入式块RAM(框)。结果表明,基于DAA的方法是适当的,并且对于少量滤波器抽头是合适的,并且基于RNS的方法对于超过10个过滤器抽头的方法是更合适的。

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