近幾年來在許多無線通訊系統對於DSP系統處理的效能要求愈來愈高之下，因此本論文中提出改良式具有高效能和低硬體架構的運算共享式可程式FIR濾波器 (Programmable FIR Filter) 。而設計FIR濾波器的方法大約有三種架構形式。第一種為共同式子分享/消除 (Common Subexpression Sharing / Elimination) 第二種為加法圖(Adder Graph)的概念，三種為差分法(Difference Method)的演算法，而我們主要是利用共同式子分享/消除之觀念，主要的想法主要是利用FIR 濾波器各個系數乘法運算中針對有共同因子的部分乘積提出來共用以達到硬體共享的情況，利用此想法提出所謂的算共享式可程式FIR濾波器來做為基礎架構並改進它。而運算共享式可程式FIR濾波器可以用來降低DSP系統內用於各種不同通訊規格上之FIR濾波器硬體的使用個數，並使系統能運用在高速度的環境下。在本文中提到(CSD，Canonic-Signed-Digit)表示法的概念設計，這個表示法能有效的降低乘法器硬體上的面積，研究中把CSD表示法運用在運算共享式乘法器並使用於FIR濾波器中，也因此濾波器架構能有效降低其硬體上之面積大小和提高工作效率，在電路功率秏損的情況下也能做改善。此外再對各種不同位元寬度預算乘法器(Pre-computer)之運算共享式可程式FIR濾波器做電路設計來分析模擬並驗證理論，而後探討不同架構下之運算共享式可程式FIR濾波器和使用CSD改良過後的設計在面積上、速度上及消秏功率上、有些何許不同。

In recent years, digital signal processing (DSP) processors which use in many of the wireless communication systems has been requested high-performance. In this thesis, we propose the high-performance and low-cost design for Computation Sharing Programmable FIR Filter. Today, there are three kinds of methods for FIR filters design. There are common subexpression sharing/elimination method [3], [4], adder graph approach method [7], [8] and difference method [6], [11]. The most commonly used is common sub- expression sharing/elimination. The idea here is to find common patterns in the representation of the multiplier coefficients. This means that the mul- tiplier partial products can be shared. We use this concept to bring up Computation Sharing Programmable FIR Filter and then we base on this architecture to improve it. The Computation Sharing Programmable FIR Filter can replace many of the FIR Filters which is used in the DSP system for different communication specifications, and it can achieve DSP system to high efficiency. In the article, we mentioned a Computation Sharing Multiplier (CSHM) which used Canonic-Signed-Digit (CSD) representation in FIR Filter design can make high performance and low complexity in application. Beside, we improve the Programmable FIR Filter for different Pre-computer bit word lengths and give simulation analysis to validate theories. Finally, we discuss the design what are the difference about the Computation Sharing Programmable FIR Filter and use CSD representation to improve it. Finally, we discuss the difference about area, power, and timing between Computation Sharing Programmable FIR Filter using CSD representation and non-use of CSD representation.

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