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Implementation of adaptive digital FIR and reprogrammable mixed-signal filters using distributed arithmetic.

机译:使用分布式算法实现自适应数字FIR和可重新编程的混合信号滤波器。

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摘要

When computational resources are limited, especially multipliers, distributed arithmetic (DA) is used in lieu of the typical multiplier-based filtering structures. However, DA is not well suited for adaptive applications. The bottleneck is updating the memory table. Several attempts have been done to accelerate updating the memory, but at the expense of additional memory usage and of convergence speed.;To develop an adaptive DA filter with an uncompromised convergence rate, the memory table must be fully updated. In this research, an efficient method for fully updating a DA memory table is proposed. The proposed update method is based on exploiting the temporal locality of the stored data and subexpression sharing. The proposed update method reduces the computational workload and requires no additional memory resources. DA using the proposed update method is called conjugate distributed arithmetic.;Filters can also be constructed from analog components. Often, for lower precision computations, analog circuits use less power and less chip area than their digital counterparts. However, digital components are often used because of their ease of reprogrammability. Achieving such reprogrammability in analog is possible, but at the expense of additional chip area.;A reprogrammable mixed-signal DA finite impulse response (FIR) filter is proposed to address the issues with reprogrammable analog FIR filters that are constructing compact reprogrammable filtering structures, non-symmetric and imprecise filter coefficients, inconsistent sampling of the input data, and input sample data corruption. These issues are successfully addressed using distributed arithmetic, digital registers, and epots.;Also, a mixed-signal DA second-order section (SOS), which is used as the building block for higher order infinite impulse response filters, was proposed. The type of issues with an analog SOS filter are similar to those of an analog FIR filter, which are the lack of a compact reprogrammable filtering structure, the imprecise filter coefficients, the inconsistent sampling of the data, and the corruption of the data samples. These issues are successfully addressed using distributed arithmetic and digital registers.
机译:当计算资源(尤其是乘法器)有限时,将使用分布式算术(DA)代替典型的基于乘法器的滤波结构。但是,DA不太适合自适应应用。瓶颈正在更新内存表。已经进行了几次尝试来加速更新存储器,但是以牺牲额外的存储器使用和收敛速度为代价。为了开发具有不妥协的收敛速率的自适应DA滤波器,必须完全更新存储器表。在这项研究中,提出了一种用于完全更新DA存储器表的有效方法。所提出的更新方法基于利用存储数据的时间局部性和子表达式共享。所提出的更新方法减少了计算工作量,并且不需要额外的内存资源。使用提出的更新方法的DA称为共轭分布算法。滤波器也可以由模拟组件构造。通常,对于较低精度的计算,模拟电路比数字电路消耗更少的功率和更少的芯片面积。但是,由于易于重新编程,因此经常使用数字组件。在模拟中实现这种可重编程性是可能的,但是要以增加芯片面积为代价。提出了一种可重编程混合信号DA有限脉冲响应(FIR)滤波器,以解决可重编程模拟FIR滤波器的问题,该滤波器构建了紧凑的可重编程滤波结构,非对称和不精确的滤波器系数,输入数据的采样不一致以及输入采样数据损坏。使用分布式算术,数字寄存器和epot成功解决了这些问题。此外,还提出了混合信号DA二阶部分(SOS),它用作高阶无限冲激响应滤波器的基础。模拟SOS滤波器的问题类型与模拟FIR滤波器的问题类型相似,它们缺乏紧凑的可重新编程滤波结构,不精确的滤波器系数,数据采样不一致以及数据样本损坏。使用分布式算术和数字寄存器已成功解决了这些问题。

著录项

  • 作者

    Huang, Walter G.;

  • 作者单位

    Georgia Institute of Technology.;

  • 授予单位 Georgia Institute of Technology.;
  • 学科 Engineering Electronics and Electrical.
  • 学位 Ph.D.
  • 年度 2009
  • 页码 157 p.
  • 总页数 157
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

  • 入库时间 2022-08-17 11:38:01

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