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研究生: 黃鈺哲
YU-ZHE HUANG
論文名稱: 應用於系統辨識之無除法器Normalized LMS適應性濾波器之硬體實現
Hardware Implementation of Dividerless Normalized LMS Adaptive Filters for System Identifications
指導教授: 姚嘉瑜
Chia-Yu Yao
口試委員: 彭盛裕
Sheng-Yu Peng
陳筱青
Hsiao-Chin Chen
學位類別: 碩士
Master
系所名稱: 電資學院 - 電機工程系
Department of Electrical Engineering
論文出版年: 2023
畢業學年度: 111
語文別: 英文
論文頁數: 109
中文關鍵詞: 適應性濾波器系統辨識FIR濾波器IIR濾波器NLMS演算法
外文關鍵詞: Adaptive Filter, System Identification, FIR Filter, IIR Filter, NLMS Algorithm
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  • 本論文提出二個不需要純量除法運算的近似 NLMS架構適應性濾波器來的設計與實現。本論文使用二進制簡化法與Canonical Signed-Digit (CSD) 簡化法來利用乘法運算來近似傳統的除法運算。在硬體優化方面,因為避免了除法的回授運算架構,可以大幅增加資料吞吐量,當與傳統除法架構相同吞吐量時,則能大幅降低面積及功耗。本論文使用FIR 架構實現近似 NLMS 演算法的適應性濾波器 VLSI 硬體,並進一步將其運用至硬體 IIR 適應性濾波器。
    本論文所提出的近似NLMS架構適應性濾波器分別在基於Altera Cyclone IV EP4CE115F29C7N的DE2-115、TSMC 90 nm CMOS元件庫實現與驗證。在FIR架構下,FPGA部分的工作頻率可以達到91 MHz,二進制簡化法使用11773個邏輯元件和2555個暫存器,其功率消耗為271.67 mW, CSD簡化法使用11897個邏輯元件和2571個暫存器,其功率消耗為271.80 mW,與傳統除法架構同工作頻率下提升至236%的吞吐量。若以TSMC 90 nm CMOS元件庫合成,工作頻率可以達到270 MHz,並具有24.55 Msamples/sec.,消耗的邏輯閘數量分別為74 KGE與75KGE,功率消耗分別為11.99 mW與 12.30 mW,一樣提升了236%的吞吐量。


    This thesis presents the design and implementation of two approximate NLMS architectures with adaptive filters that do not require division operations. This work uses binary simplification and canonical signed digit (CSD) simplification to replace the conventional division algorithm by using multiplication. When implemented in hardware, it can increase the throughput rate with the same clock frequency as the conventional division architecture, or reduce the clock rate and power consumption with a similar throughput rate as the conventional division architecture. In this work, we use the FIR architecture to implement the hardware for the approximate NLMS algorithm and further apply it to the adaptive IIR filter hardware.
    The proposed approximate adaptive NLMS filters have been implemented and verified on the Altera Cyclone IV EP4CE115F29C7N-based DE2-115 FPGA board and in the TSMC 90 nm CMOS cell library. With the FIR architecture, the DE2-115 can operate at a clock rate of 91 MHz. The binary simplification uses 11773 logic components and 2555 registers, and the power consumption is 271.67mW. The CSD simplification uses 11897 logic components and 2571 registers, and the power consumption is 271.80 mW. The throughput rate can be increased to 236% at the same clock rate compared with the conventional NLMS-FIR architecture with 16-bit SRT division. Synthesized in TSMC 90nm CMOS cell library, the clock rate can reach 270MHz and the throughput rate can reach 24.55 Msamples/s. The gate count is 74 KGE and 75 KGE, and the power consumption is 11.99 mW and 12.30 mW, respectively.

    Table of Contents 摘要 I Abstract II 誌謝 III Table of Contents IV List of Figures VI List of Tables XV Chapter 1 Introduction 1 1.1 Motivation 1 1.2 Organization of the Thesis 2 Chapter 2 Theory 3 2.1 System Identification with Normalized LMS Algorithm 3 2.1.1 FIR Structure 3 2.1.2 IIR Structure 5 2.2 Newton-Raphson Algorithm 7 2.3 Radix-2 SRT Algorithm 8 Chapter 3 Proposed Methods 11 3.1 Binary Form Simplification 12 3.2 CSD Form Simplification 13 3.3 Partial SRT Simplification 14 Chapter 4 Hardware Design 15 4.1 NLMS Adaptive FIR Filter 15 4.2 NLMS Adaptive IIR Filter 16 4.3 Wallace Adder Tree 18 4.4 Radix-8 Booth Multiplier 19 4.4.1 Radix-8 Booth Encoder 21 4.4.2 Partial Product Addition 22 4.5 Scaling Factor Generator 24 4.6 CSD Convert Circuit 26 4.7 Multiplication of a 2’s Complement Number and a CSD Number 28 4.8 Conversion of Division to Multiplication 29 4.9 SRT Divider 32 Chapter 5 Experiment Results 34 5.1 Design Flow 34 5.2 NLMS Adaptive FIR Filter 35 5.3 NLMS Adaptive IIR Filter 45 5.4 FPGA Verification 73 5.5 IP Implementation 82 Chapter 6 Conclusion 90 6.1 Conclusion 90 6.2 Future Works 90 References 92

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