在臨界值邏輯的理論中，臨界值函數的辨別方法是一個基本卻很重要的工作，它可以決定一個布林函數是否可以被單一臨界值邏輯閘呈現。在此理論中，藉由建立非冗餘的不等式系統與全面性權重分配，我們提出一個更有效率與效能的臨界值邏輯函數辨別演算法。這是第一個可以辨別所有8輸入臨界值函數的非整數線性規劃的演算法。從實驗結果中，我們顯示出提倡的方法比所有現存的非整數線性規劃方法更加有效，以及提倡的方法產生出的臨界值邏輯閘有將近100%的機率會是最佳的。對於9到15輸入臨界值函數，提倡的方法也可以在合理的執行時間內，辨別出所有由隨機產生的100,000個臨界值函數。

The identification of threshold function, which determines whether a Boolean function can be represented by an LTG or not, is a fundamental but important task in the theories of threshold logic. In this thesis, we propose a more efficient and effective algorithm of threshold function identification by constructing the system of irredundant inequalities and adjusting the weight assignment comprehensively. This is the first non-ILP-based approach that is able to identify all the 8-input threshold functions. The experimental results demonstrated that the proposed approach is more effective than all the existing non-ILP-based approaches and the LTGs obtained by the proposed approach are optimal for near 100\% cases. For threshold functions with 9 to 15 inputs, the proposed approach can identify 100,000 randomly generated threshold functions as well in a reasonable CPU time.

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