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研究生： Le Huu Ton
Le - Huu Ton
論文名稱： A Novel Fixed-point FIR Filter Design and Implementation Method in the Expanding Sub-expression Space
A Novel Fixed-point FIR Filter Design and Implementation Method in the Expanding Sub-expression Space
指導教授： 姚嘉瑜
Chia-Yu Yao
口試委員: 韓永祥
Yunghsiang S. Han
郭景明
Jing-Ming Guo
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： 2011
畢業學年度： 99
語文別： 英文
論文頁數： 91
中文關鍵詞： Fixed-point FIR filter 、Expanding Sub-expression Space
外文關鍵詞： Fixed-point FIR filter, Expanding Sub-expression Space
相關次數： 點閱：345  下載：2 
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  •  上一筆

    • This thesis presents a new method for designing fixed-point FIR filters. In the proposed method, both magnitude response and hardware cost are taken into consideration in the design process. The idea of the common sub-expression sharing method is applied by determining a basic set and expanding this basic set gradually. In addition, to deal with long filters, some strategies that aim to speed up the program are also employed. The experimental results of several benchmark examples show that by applying the proposed method, we can obtain the second best results, in an acceptable run time than the best results of published papers.

    Abstract I Acknowledgement II Table of Contents III List of Fig.s IV List of Tables VIII Chapter 1 Introduction 1 1.1 Introduction to digital filters 1 1.2 Background and motivation 1 1.3 Overview of the proposed method 4 Chapter 2 Theory 5 2.1 FIR filters structure 5 2.2 Common sub-expression sharing method 8 2.2.1 Introduction to the common sub expression sharing method 8 2.2.2 Sub-expression space 9 Chapter 3 Proposed Method 11 3.1 Finding of the floating point coefficient 11 3.2 Sorting of the coefficients 12 3.3 Branch and bound algorithm 12 3.3.1 Finding of the upper bound and lower bound of each coefficient 13 3.3.2 Replacing of the floating point coefficient by fix-point coefficient. 15 3.3.3 Checking the zero coefficient 17 3.3.4 Expanding the basic set 20 3.4 Speeding up the algorithm. 21 3.4.1 Choosing a suitable pass band gain g 21 3.4.2 Prediction strategy 23 3.4.3 Dealing with long FIR filter 24 3.5 Algorithm flow chart and a work out example 26 3.5.1 Algorithm flow chart 26 3.5.2 A work-out example 30 Chapter 4 Experiment result and comparison 33 Chapter 5 Conclusion and future work 38 Appendix 40 A.1 Choose the pass band gain g using method 1 40 A.2 Choose the pass band gain g using method 2 56 A.3 Choose the pass band gain g using method 3 72 References 88

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