基于位切片乘法器的FFT与线性卷积实现：一种新方法
FFT and Linear Convolution Implementation with Bit Slicing Multiplier: A Novel Approach
AI总结：
本文提出将位切片乘法器（BSM）集成到FFT和线性卷积中，利用LUT并行按位运算提升FPGA信号处理的速度与资源效率，并通过Vivado实验验证其优越性。
摘要：
本文对快速傅里叶变换（FFT）和线性卷积的实现进行了全面探索，融合了传统方法与利用位切片乘法器（BSM）技术的新方法。位切片乘法器利用查找表（LUT）并行执行按位运算，提供适合数字信号处理任务的高效算术运算。我们深入研究了将BSM集成到FFT和线性卷积算法中的方法，重点强调其在速度和资源利用率方面的优势。此外，我们提出了自己针对FFT和卷积算法的创新思路，为高效信号处理技术的更广泛讨论做出贡献。我们使用领先的FPGA综合与实现工具Vivado对所提出的实现进行了实验验证。对比分析表明，我们基于BSM增强的方法具有优越性能，展示了其在实时信号处理应用中的潜力。本研究不仅推进了对FFT和卷积实现的理解，也凸显了BSM等新技术在提升基于FPGA系统的计算效率方面的有效性。
英文摘要：
This paper presents a comprehensive exploration of Fast Fourier Transform (FFT) and linear convolution implementations, integrating both conventional methods and novel approaches leveraging the Bit Slicing Multiplier (BSM) technique. The Bit Slicing Multiplier utilizes Look-Up Tables (LUTs) to execute bitwise operations in parallel, offering efficient arithmetic operations ideally suited for digital signal processing tasks. We extensively investigate the integration of BSM into FFT and linear convolution algorithms, emphasizing its advantages in terms of speed and resource utilization. Additionally, we introduce our own innovative ideas for FFT and convolution algorithms, contributing to the broader discourse on efficient signal processing techniques. Experimental validation of our implementations is conducted using Vivado, a leading FPGA synthesis and implementation tool. Comparative analysis demonstrates the superior performance of our BSM-enhanced approaches, showcasing their potential for real-time signal processing applications. This study not only advances the understanding of FFT and convolution implementations but also highlights the effectiveness of novel techniques like BSM in enhancing computational efficiency in FPGA-based systems.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
