摘要翻译：
本研究工作主要针对高分辨率快速傅里叶变换(FFT)/快速傅里叶逆变换(IFFT)处理器的设计进行研究。高分辨率FFT处理器的主要缺点是浮点计算的结构复杂性和计算效率低所导致的高功耗。因此，提出了一种并行流水线结构来静态地扩展处理器的分辨率，以满足充分的权衡约束。该量化被应用于解决数字信号处理(DSP)的有限字长约束提供一种近似。提出了一种基于信噪比(SQNR)和量化统计理论的最佳工作模式，以最大限度地减少与选择最有效的浮点处理能力相对于分辨率质量的折衷问题。
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英文标题：
《Static Quantized Radix-2 FFT/IFFT Processor for Constraints Analysis》
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作者：
Rozita Teymourzadeh, Mometo Jim Abigo, Mok Vee Hoong
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最新提交年份：
2018
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分类信息：

一级分类：Electrical Engineering and Systems Science        电气工程与系统科学
二级分类：Signal Processing        信号处理
分类描述：Theory, algorithms, performance analysis and applications of signal and data analysis, including physical modeling, processing, detection and parameter estimation, learning, mining, retrieval, and information extraction. The term "signal" includes speech, audio, sonar, radar, geophysical, physiological, (bio-) medical, image, video, and multimodal natural and man-made signals, including communication signals and data. Topics of interest include: statistical signal processing, spectral estimation and system identification; filter design, adaptive filtering / stochastic learning; (compressive) sampling, sensing, and transform-domain methods including fast algorithms; signal processing for machine learning and machine learning for signal processing applications; in-network and graph signal processing; convex and nonconvex optimization methods for signal processing applications; radar, sonar, and sensor array beamforming and direction finding; communications signal processing; low power, multi-core and system-on-chip signal processing; sensing, communication, analysis and optimization for cyber-physical systems such as power grids and the Internet of Things.
信号和数据分析的理论、算法、性能分析和应用，包括物理建模、处理、检测和参数估计、学习、挖掘、检索和信息提取。“信号”一词包括语音、音频、声纳、雷达、地球物理、生理、（生物）医学、图像、视频和多模态自然和人为信号，包括通信信号和数据。感兴趣的主题包括：统计信号处理、谱估计和系统辨识；滤波器设计；自适应滤波/随机学习；（压缩）采样、传感和变换域方法，包括快速算法；用于机器学习的信号处理和用于信号处理应用的机器学习；网络与图形信号处理；信号处理中的凸和非凸优化方法；雷达、声纳和传感器阵列波束形成和测向；通信信号处理；低功耗、多核、片上系统信号处理；信息物理系统的传感、通信、分析和优化，如电网和物联网。
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一级分类：Computer Science        计算机科学
二级分类：Hardware Architecture        硬件体系结构
分类描述：Covers systems organization and hardware architecture. Roughly includes material in ACM Subject Classes C.0, C.1, and C.5.
涵盖系统组织和硬件架构。大致包括ACM主题课程C.0、C.1和C.5中的材料。
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英文摘要：
  This research work focuses on the design of a high-resolution fast Fourier transform (FFT) /inverse fast Fourier transform (IFFT) processors for constraints analysis purpose. Amongst the major setbacks associated with such high resolution, FFT processors are the high power consumption resulting from the structural complexity and computational inefficiency of floating-point calculations. As such, a parallel pipelined architecture was proposed to statically scale the resolution of the processor to suite adequate trade-off constraints. The quantization was applied to provide an approximation to address the finite word-length constraints of digital signal processing (DSP). An optimum operating mode was proposed, based on the signal-to-quantization-noise ratio (SQNR) as well as the statistical theory of quantization, to minimize the tradeoff issues associated with selecting the most application-efficient floating-point processing capability in contrast to their resolution quality.
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PDF链接：
https://arxiv.org/pdf/1806.03716