隨著製程技術的進步，晶片發生錯誤的可能性提升，對於硬體設計者而言，能夠在晶片製造前模擬晶片可能的錯誤情形，並找出潛在的錯誤位置是其重要的考量。因此對於硬體設計者而言，會盡可能的模擬所有可能發生的錯誤並避免晶片製造後產生錯誤結果，以至於提高晶片製造時的良率。但是對於規模較大電路而言，其潛在的錯誤位置數量眾多，且要以邏輯閘層級執行所有錯誤模擬，模擬所需的時間會是必須面臨的議題。
本研究建構一個在行為描述層級上的錯誤模擬平台，相較於邏輯閘層級模擬，本研究減少了99%的模擬使用時間，並且建立一行為描述層級與邏輯閘層級間的對照關係，由於考量模擬時間及錯誤嚴重程度，我們選擇單一固接錯誤為錯誤模型實現。
本研究以JPEG2000影像壓縮標準為平台實驗對象，我們產生多種影像錯誤特徵以供影像品質評估參數開發者做為考量，且分析其錯誤模擬結果。藉由分析影像錯誤特徵發現，若於影像特殊應用(如邊緣偵測)中以影像品質評估參數為晶片判定標準，會將許多實際能夠使用的電路歸類為不能使用，而在我們的模擬平台可以提前分析此類錯誤特徵以提高有效良率。且我們分析JPEG2000中個別區塊存在錯誤時對於影像的錯誤嚴重程度，可將JPEG2000中的電路區塊以錯誤嚴重程度分級，且找出負責壓縮與編碼的熵編碼為受錯誤影響較嚴重區塊，以在硬體設計前針對特定區塊加入電路保護設計。

With the manufacturing technology advances, errors are more likely to occur in manufactured chips. As a result, locating potential fault sites and evaluating severity of errors become more critical. These analytical results are beneficial to help improve chip yield and also enhance chip reliability. However, long simulation time is usually required to perform such analysis. In this thesis, we address this issue by proposing a behavior-level simulation platform. Using this platform to perform fault analysis can save 99% simulation time when compared with gate-level simulation. To make the simulation based on the proposed platform practical, we carefully consider the fault effect correlations between behavior-level and gate-level. This makes the fault analysis results obtained by the proposed platform can be close to those obtained at gate-level. In our consideration, the single stuck-at fault model is employed. In our platform, automation methods are also developed to make the analysis process more efficient.
For the purpose of illustration, the JPEG2000 image encoder is used in this thesis to demonstrate the effectiveness of the proposed platform. Based on our platform, we can easily generate various erroneous images caused by injecting various faults in the JPEG2000 encoder. Our platform also integrates several types of image quality evaluation method to analyze quality of these erroneous images. These erroneous images can also serve as a database that will be useful when a new image quality evaluation parameter is to be developed. The quality evaluation results are beneficial to help analyze the severity of the associated faults. Accordingly the criticality of each part of the image encoder can be determined. Selective hardening methods can then be applied to protect critical hardware parts for saving hardware cost.

致謝 i
摘要 ii
Abstract iii
目 錄 iv
圖目錄 vi
表目錄 vii
第一章 緒論 1
研究背景與動機 1
研究貢獻 2
論文大綱 3
第二章 背景及相關文獻回顧 4
相關文獻回顧 4
行為描述層級(Behavior-Level) 4
容誤(Error Tolerance)[4,5] 5
錯誤模型(Fault Model) 5
影像格式 7
JPEG2000影像壓縮標準 8
前處理 9
離散小波轉換 10
量化 11
內嵌區塊編碼(EBCOT) 12
內容統計編碼(Context Formation) 13
算術編碼(Arithmetic Coding) 15
Tier-2編碼器 15
第三章 實驗流程與模擬平台開發 16
模擬環境 16
Powershell批次執行 18
插入錯誤程式及其考量 19
算術運算 20
條件執行 21
函式 22
錯誤插入方式 24
編譯與執行 26
平台考量與應用 27
第四章 實驗流程與結果分析 28
實驗流程 28
影像品質評估參數 28
測試影像 31
錯誤特徵分析 32
JPEG2000錯誤分析 41
錯誤影像用於影像品質評估參數開發 42
第五章 平台應用探討及考量 49
System C使用考量 49
JPEG2000解碼器於平台應用 49
第六章 結論 50
參考文獻 51

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