大部的類神經網路均為解決特定問題而設計，並非真正去模擬人腦的功能 ，在本論文中介紹一個模擬人類學習方式的類神經網路，稱為推理類神經 網路（The Reasoning Neural Network），其主要兩個組成為強記（ cram -ming）及推理（reasoning）部份，透過彈性的組合這兩個部份可 使類神經網路具有類似人類的學習程序。在本論文中介紹其中一個學習程 序並用四個實驗來評估推理類神經網路的績效，從實結果得知，推理類神 經網路能以合理的隱藏節點數（hidden nodes）達到學習的目標，並建立 一個網路內部表示方式（internal representation），及具有好的推理 能力（g eneralization ability）。 / Most of artification Neural Networks are designed to resolve spe -cific problems, rather than to model the brain. The Reasoning N -eural Network (RNN) that imitates the way of human learning is presented here. Two key components of RNN are the cramming and t -he reasoning. These components coulds be arranged flexibly to a -chieve the human-like learning procedure. One edition of the RNN used in experiments is introduces, and four different proble -ms are used to evaluate the RNN's performance. From simulation results, the RNN accomplishes the goal of learning with a reason -able number of hidden nodes, and evolves a good internal repres -entation and a generalization ability.

依時間順序出現之一連串觀測值，通常會呈現某一型態，而根據所產生的 型態可以作為判斷事件發生的基礎。例如，震波形成原因的判斷﹔追查環 境污染源﹔以及在醫學方面，辨識一個正常人心電圖的型態與患有心臟病 的病人其心電圖的型態…等。對於這些問題，傳統之辨識方法常因前提假 設的限制而失去其準確性。在本文中，我們應用神經網路中的逆向傳播演 算法則來訓練網路，並利用此受過訓練的網路來辨別線性時間數列ARIMA 及非線性時間數列 BL(1,0,1,1)。結果發現，網路對於模擬資料中雙線性 係數介於0.2至$0.8$之間的資料有高達$80\%$以上的辨識能力。而在實例 研究中，我們訓練網路來判斷震波形成的原因，其正確率亦高達80\%以上 。同時，我們也將神經網路應用在環境保護方面，訓練網路來判斷二地區 空氣品質的型態。 / A series of observations indexed in time often produces a pattern that may form a basis for discriminatingetween different classes of events. For instance, in theeology, what are the causes of seismic waves? a earthquakesr the nuclear explosions ?in the eathenics, we can use theethod to inquire the source which pollutes the air in somelace, and in the medicine, to distinguish the difference oflectrocardiograms between a health person and an a patient..ect. In this paper, we utilize the back-propagation to trainnetwork and use of the trained networks to judge the linearRIMA(1,0,0) model between the nonlinear BIL(1,0,1,1) model,e can find that the trained network has a good recognitionhose accurate rate is above 80\% for the coefficient of the bilinear model being equal to 0.5 or 0.8. In a living example, we have trained a network to decidehich is the cause of seismic wave, and the trained networkhose accurate rate is larger than 80\%. At the same time, e also applied neural network in environmental protection.

線性迴歸模型中共線性的問題是導致模型不適當的重大原因之一。共線性 的存在不止會影響到參數的估計，使參數的變異變大，還會妨礙我們評估 自變數對模型重要性的能力，甚至會使我們忽略或去除掉重要的自變數。 而變異膨脹因子是診斷線性迴歸模型共線性問題時常用而有效的方法之一 ，但它只是考慮單一自變數的情況。本文則對於模型同時加入一組自變數 時影響原模型共線性的問題，先推導出廣義的判定係數，再利用它推導出 變異膨脹矩陣。再應用這個變異膨脹矩陣發展出六個準則，使得變異膨脹 矩陣有一個單一的指標來對模型的共線性做診斷。最後並以一個例子以實 際的數據，用六個準則對不同的模型做診斷，並嘗試找出各準則的指標。

指數型基金透過追蹤指數來提供投資人被動管理的投資策略，因而成為保守投資人的熱門投資工具。本論文的目的在於建立一個追蹤指數的同時也能有效控管損失的指數型基金。在此目標下，該基金面臨到的不單是追蹤指數的績效，還有降低資產配置風險的問題。有鑑於此，本論文融合兩種下方風險的概念：指數追蹤的下方偏差(downside absolute deviation)以及條件風險值(conditional value-at-risk, CVaR)。針對兩者間的規避程度分別分配其權重，並以該基金之平均報酬大於指數的平均報酬作為限制條件，經由改寫下方偏差與離散化CVaR後得到一個新的線性規劃模型。本論文以台灣50指數與恆生指數的歷史資料做為實證探討的對象，驗證使用本線性規劃模型所建立之指數型基金的效能。 / Index fund has become popular in these days among the conservative investors since it provides a passive investment strategy. The main purpose of this paper is to create an index fund which can replicate the performance of a broad-based index of stocks and has the ability to control the loss efficiently at the same time. For this purpose, the index fund we build confronts with not only the performance of index tracking, but also lowering the level of the risk of assets allocation. In order to accomplish the goal, we combine two concepts of downside risk: downside absolute deviation and conditional value-at-risk (CVaR). Under the constraint of average portfolio return being greater than average index return, and assign weights according to the degree of evasion to each of the risks, a linear programming model is formulated by rewriting downside absolute deviation and discretizing CVaR. The results obtained from the computational experience on Taiwan 50 index and Hang Seng index are provided for testing the efficiency of this model.

在解釋變數含測量誤差的簡單線性迴歸模式中，欲使第t+1期之產出Y達到某一目標值Y^*，則必需控制第t+1期投入變數Z，若參數α，β為以知時，可以將其設定為θ=(Y^*-α)/β。但當參數α，β為未知時，我們利用LSCE控制法則的設定方法，得到第t+1期設定的控制值Z_t+1，而且在機率為1下，Z_t+1 收斂至θ=(Y^*-α)/β。而貝氏最佳控制法則部份則是由第t+1期的預測期望損失，找出使其為最小的Z值即是所應設定的第t+1期控制值Z_t+1，並利用模擬結果來說明。

在傳統的簽章機制中，我們需要一個具有公信力的第三方 (Trusted Third Party, TTP) 來核發數位憑證，以驗證公開金鑰確實屬於簽章者所擁有，為了減少TTP的負擔，於是就有學者提出了免憑證簽章 (Certificateless Signature) 機制。另一方面，具有訊息回復 (Message Recovery) 功能的數位簽章是指原始訊息不需要與簽章一起傳送給接收者以簡化訊息及簽章在傳送時的長度。 本論文中我們提出了一個具有訊息回復功能的免憑證簽章機制，和一般簽章方式相比，我們的方法不僅具有免憑證簽章的優點，訊息回復功能也減少了訊息和簽章的總長度，提昇了訊息的傳送效率 (Communication Cost)，在效能方面也有不錯的表現，因此非常適用於以頻寬為主要考量的公司組織以及對短訊息作簽章的應用，最後我們也有對我們的簽章方法做完整的安全性證明。 / In traditional digital signature systems, a trusted third party (TTP) is required in order to issue a digital certificate. The certificate is to assure that the public key actually belongs to the person of the signature. In order to reduce the burden of TTP, some scholars proposed the Certificateless Signatures. On the other hand, a digital signature with message recovery is a signature that the message itself is not required to be transmitted together with the signature. It has the advantage of small data size of communication. In this paper, a certificateless signature with message recovery is proposed. It inherits both the advantages of certificateless signatures and signatures providing message recovery. The performance of our scheme is compared with other schemes which shows that our scheme is quite efficient and the security of the scheme is finally proved in the random oracle model.

本論文提出利用機率平賭性質由選擇權市場價格還原風險中立機率測度的雙目標規劃模型。假設對應同一標的資產且不同履約價的選擇權均為歐式選擇權，到期時標的資產的狀態為離散點且個數有限。若市場不存在套利機會時，建構出最小化離差總和及最大化平滑的雙目標規劃模型。將此雙目標規劃模型利用權重法轉換成單一目標之非線性模型，即可還原風險中立機率測度，並利用此風險中立機率測度評價選擇權的公平價格。最後，我們以台指選擇權(TXO)為例，驗證此模型的評價能力。 / This thesis proposes a biobjective nonlinear programming model to derive risk-neutral probability distribution of underlying asset. The method are used to choose probabilities that minimize the deviation between the observed price and the theoretical price as well as maximize the smoothness of the resulting probabilities. A weighting method is used to covert the model into a single objective model. Given a non-arbitrage observed option price, a risk-neutral probability distribution consistent with the observed option can be recovered by the model. This risk-neutral probability is then utilized to evaluate the fair price of options. Finally, an empirical study applying to Taiwan’s market is given to verify the pricing ability of this model.

意識的議題古老而難解，但是近年來認知神經科學領域對此議題的探討已經熱烈展開，本研究之主要目的即在探索視覺意識與大腦功能性連結之間的關係。 根據一項人臉知覺的實驗結果，本研究依照線性對非線性、局部對整體等兩項條件所構成的四個取向，分別擬定用以反映視覺意識的腦電波指標。結果發現，線性的局部指標—即γ波的強度，以及線性的整體指標—即γ波的相位耦合程度，兩者皆無法有效反映視覺意識。然而，非線性的局部指標—即吸子的相關維度，在特定通道上可以反映視覺意識；至於非線性的整體指標—即廣義的同步化程度，乃為四者中最能穩定反映視覺意識的指標。 除了得到上述若干可以有效反映視覺意識的腦電波指標之外，本研究實質上整合了認知神經科學、非線性動力系統理論、小波轉換理論以及小世界理論等當代思維，因此文中亦做出大量而深入的理論探討，並且提出對現有相關研究在邏輯或方法上的改進與澄清。 / Consciousness is an ancient and puzzling mystery. Until recently, scientists have made little significant progress on it. This study is aimed to search for the neural correlates of visual awareness. / Based on empirical data from an experiment of face perception, this study explores linear vs. nonlinear and local vs. global human EEG indexes of visual awareness. The results indicate that neither linear local index, i.e. γ-band power, nor linear global index, i.e. γ-band phase coherence, can reveal the participant’s state of awareness validly. However, nonlinear local index, i.e. correlation dimension of attractor, can be a valid index of visual awareness, but only on specific channels. Last but not least, nonlinear global index, i.e. generalized synchrony, can be the most valid and efficient index of visual awareness. / In addition to the empirical findings listed above, this study, an interdisciplinary combination of cognitive neuroscience, chaos theory, wavelet transform and small-world theory, also presents numerous theoretical discussions and modifications to other related studies logically or methodologically.

投資者面對到期日相同的ㄧ序列不同履約價格的選擇權，已有許多文獻提出如何建立選擇權最佳投資組合，但模型中均未考慮交易成本。選擇權在實際市場的交易過程中，投資者所支付的手續費與賦稅即為選擇權的交易成本。本論文針對買賣到期日相同但不同履約價格的買權與賣權如何組合，提出考慮交易成本的整數線性規劃模型，建立選擇權最佳交易策略。我們不考慮股價變動的機率分配型態，延伸楊靜宜 (2004)所建立之整數線性規劃模型和Liu與Liu (2006)的大中取小模型，建構考慮比例制、固定制與混合制交易成本之整數線性規劃模型。最後，我們以台指選擇權(TXO)為例，驗證模型的效能。 關鍵字：交易成本，選擇權交易策略，整數線性規劃，選擇權套利機會。 / There are many researchers focus on constructing the optimal strategies and propose integer linear programming (ILP) for a series of options which are on the same maturity date with different strike price, but they neglect transaction costs in their models. The transaction costs of options are the handling charge and taxes which investors should pay for trading in the market. The thesis proposes an ILP with transaction costs to construct the optimal strategy for an option portfolio of call- and put- options on the same maturity date with different strike price. We leave the distribution of the variety of stock price out of consideration and extend Yang’s (2004) model and Liu & Liu’s (2006) min-max regret model to construct ILP with proportional, fixed, and mixed transaction costs. Finally, we take the trading data of TXO as an empirical study to test and verify the efficiency of our models. Key words: transaction costs, option trading strategies, integer linear programming, option arbitrage opportunities.

本論文研究如何由觀測的選擇權市場價格還原風險中立機率測度（等價平賭測度）。首先建構選擇權投資組合的套利模型，其中假設選擇權為單期，到期日時的狀態為離散點且個數有限，並且對應同一標的資產且不同履約價格。若市場不存在套利機會時，可使用拉格朗日乘數法則將選擇權套利模型導出拉格朗日乘子的可行性問題。將可行性問題作為限制式重新建構線性規劃模型以還原風險中立機率測度，並且利用此風險中立機率測度評價選擇權的公正價格。最後，我們以台指選擇權（TXO）為例，驗證此模型的評價能力。 / This thesis investigates how to recover the risk-neutral probability (equivalent martingale measure) from observed market prices of options. It starts with building an arbitrage model of options portfolio in which the options are assumed to be in one-period time, finite discrete-states, and corresponding to the same underlying asset with different strike prices. If there is no arbitrage opportunity in the market, we can use Lagrangian multiplier method to obtain a Lagrangian multiplier feasibility problem from the arbitrage model. We employ the feasibility problem as the constraints to construct a linear programming model to recover the risk-neutral probability, and utilize this risk-neutral probability to evaluate the fair price of options. Finally, we take TXO as an example to verify the pricing ability of this model.