本文選題：憶阻器復(fù)合電路 + 瞬時(shí)狀態(tài)��； 參考：《西南大學(xué)》2017年碩士論文

【摘要】：鑒于憶阻器件的優(yōu)良特性,如納米級(jí)尺寸、非易失性、阻值可變等,有關(guān)它的研究不斷增加,已有多種單個(gè)或多個(gè)憶阻器結(jié)構(gòu)與先進(jìn)的CMOS技術(shù)相結(jié)合,模擬實(shí)現(xiàn)神經(jīng)形態(tài)網(wǎng)絡(luò)中的突觸或信號(hào)處理系統(tǒng)中的計(jì)算單元等。憶阻器在諸多領(lǐng)域具有應(yīng)用潛能,尤其是其復(fù)合電路,但由于憶阻器的阻值變化與其極性和初始狀態(tài)有關(guān),多個(gè)憶阻器電路行為將變得復(fù)雜并難于預(yù)測(cè)。因此,為了更好理解憶阻器復(fù)合電路行為及其特性,探究不同連接方式的憶阻器電路特性是很重要的。而憶阻器的尺寸參數(shù)變化對(duì)其阻值和特性有明顯影響,因而,為了提高憶阻器在各應(yīng)用中的準(zhǔn)確性和有效性,憶阻器電路的故障診斷是非常需要的,并且故障診斷是電路設(shè)計(jì)和測(cè)試中非常關(guān)鍵的環(huán)節(jié)。本文深入探究了多個(gè)憶阻器的復(fù)合電路特性,并分析比較了多種憶阻突觸。然后,將靈敏度分析和模糊分析相結(jié)合的方法,用于診斷憶阻器復(fù)合電路和憶阻突觸電路的故障。具體來(lái)說(shuō),本文的主要內(nèi)容可分為如下幾個(gè)部分:(1)先從物理角度,介紹了三種憶阻器模型的物理機(jī)制,包括TiO2、WOx以及Ag2S憶阻器。然后,從數(shù)學(xué)建模角度,介紹了憶阻器的兩種數(shù)學(xué)建模方式,即導(dǎo)電通道的長(zhǎng)度作為狀態(tài)變量和導(dǎo)電通道的面積作為狀態(tài)變量,并利用Matlab對(duì)已數(shù)學(xué)建模的憶阻器模型進(jìn)行仿真實(shí)驗(yàn)。(2)探究了憶阻器復(fù)合電路的特性,包括串聯(lián)、并聯(lián)和混聯(lián)結(jié)構(gòu)。分析了憶阻器電路的瞬時(shí)狀態(tài)和穩(wěn)定狀態(tài),給出了從瞬時(shí)狀態(tài)達(dá)到穩(wěn)定狀態(tài)的條件。然后,針對(duì)憶阻器的三種不同連接結(jié)構(gòu),進(jìn)行了具體地分析,給出了不同復(fù)合結(jié)構(gòu)的磁通量與電荷量之間的關(guān)系,進(jìn)而得到其等效憶阻值與磁通量或電荷量之間的關(guān)系。在此基礎(chǔ)上,研究了具有n個(gè)憶阻器的電路結(jié)構(gòu)。同時(shí),也利用相應(yīng)電路結(jié)構(gòu)的實(shí)驗(yàn)結(jié)果來(lái)說(shuō)明相關(guān)推導(dǎo)的準(zhǔn)確性。(3)基于憶阻器復(fù)合電路的理論推導(dǎo),對(duì)比分析了多種基于憶阻器的突觸。詳細(xì)推導(dǎo)了這些突觸中憶阻器阻值與輸入激勵(lì)的關(guān)系,進(jìn)而分析了實(shí)現(xiàn)的突觸權(quán)值是否是線性更新的,并通過(guò)仿真實(shí)驗(yàn)進(jìn)行了驗(yàn)證。進(jìn)一步,推導(dǎo)了憶阻值改變與所加外部激勵(lì)的時(shí)間關(guān)系。此外,分析了厚度偏差對(duì)憶阻器特性的影響,進(jìn)而探究了其對(duì)憶阻突觸的影響。(4)設(shè)計(jì)了具有反饋控制的雙發(fā)生器,能根據(jù)輸出反饋控制開關(guān)脈沖,進(jìn)而自動(dòng)切斷激勵(lì)的輸入。然后,介紹了故障診斷假說(shuō),并且基于模糊分析,推導(dǎo)出故障診斷假說(shuō)的模糊表達(dá)式。其次,利用結(jié)點(diǎn)電壓靈敏度分析與模糊分析相結(jié)合的方法,診斷憶阻器復(fù)合電路的故障。進(jìn)一步,通過(guò)兩個(gè)例子來(lái)說(shuō)明此方法在憶阻器電路診斷中的有效性。
[Abstract]:In view of the excellent characteristics of the device, such as nanometer size, nonvolatile, variable resistance and so on, the research on it has been increasing, and many single or multiple memristors have been combined with advanced CMOS technology. The synapses or signal processing units in neural morphological networks are simulated. The resistor has the potential to be applied in many fields, especially its compound circuit. However, because the resistance of the resistor is related to its polarity and initial state, the behavior of the multiple circuits will be complicated and difficult to predict. Therefore, in order to better understand the behavior and characteristics of the circuit, it is very important to explore the characteristics of the circuit with different connection modes. The resistor's dimension parameter change has obvious influence on its resistance value and characteristic. Therefore, in order to improve the accuracy and effectiveness of the device in every application, it is very necessary to diagnose the trouble of the circuit. And fault diagnosis is very important in circuit design and testing. In this paper, the compound circuit characteristics of multiple amnesia are studied, and the synapses of multiple amnesia are analyzed and compared. Then, the sensitivity analysis and fuzzy analysis are combined to diagnose the fault of the compound circuit and the synaptic circuit. Specifically, the main contents of this paper can be divided into the following parts: 1) first of all, from the physical point of view, the physical mechanisms of three kinds of memristor models, including TiO2WO x and Ag2S resistor, are introduced. Then, from the point of view of mathematical modeling, this paper introduces two mathematical modeling methods of the resistor, that is, the length of the conductive channel as the state variable and the area of the conductive channel as the state variable. Matlab is used to simulate the mathematical model of the resistor. (2) the characteristics of the compound circuit are explored, including series, parallel and hybrid structure. The transient state and the stable state of the circuit are analyzed, and the conditions for achieving the stable state from the instantaneous state are given. Then, the relationship between magnetic flux and charge of different composite structures is given, and the relationship between equivalent memory resistance and magnetic flux or charge is obtained. On the basis of this, the circuit structure with n resistive devices is studied. At the same time, the experimental results of the corresponding circuit structure are used to illustrate the accuracy of the related derivation. (3) based on the theoretical derivation of the compound circuit of the memory device, the synapses based on the memory device are compared and analyzed. The relationship between the resistive resistance and the input excitation in these synapses is deduced in detail, and then whether the realized synaptic weight is linearly updated is analyzed and verified by simulation experiments. Furthermore, the temporal relationship between the change of amnesia resistance and the external excitation is deduced. In addition, the influence of thickness deviation on the characteristics of amnesia is analyzed, and its effect on the synapse of amnesia is explored. A double generator with feedback control is designed, which can control the switch pulse according to the output feedback, and then cut off the excitation input automatically. Then, the fault diagnosis hypothesis is introduced, and the fuzzy expression of fault diagnosis hypothesis is derived based on fuzzy analysis. Secondly, using the method of node voltage sensitivity analysis and fuzzy analysis, the fault of compound circuit of amnesia is diagnosed. Furthermore, two examples are given to illustrate the effectiveness of this method in the diagnosis of resistive circuits.
【學(xué)位授予單位】：西南大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：TN60

【參考文獻(xiàn)】

相關(guān)期刊論文 前6條

1 郭羽泉;段書凱;王麗丹;;納米級(jí)尺寸參數(shù)對(duì)鈦氧化物憶阻器的特性影響[J];物理學(xué)報(bào);2015年10期

2 董哲康;段書凱;胡小方;王麗丹;;兩類納米級(jí)非線性憶阻器模型及串并聯(lián)研究[J];物理學(xué)報(bào);2014年12期

3 田曉波;徐暉;李清江;;橫截面積參數(shù)對(duì)鈦氧化物憶阻器導(dǎo)電特性的影響[J];物理學(xué)報(bào);2014年04期

4 張旭;周玉澤;閉強(qiáng);楊興華;俎云霄;;有邊界條件的憶阻元件模型及其性質(zhì)[J];物理學(xué)報(bào);2010年09期

5 胡梅;王紅;楊士元;胡庚;;基于電壓增量的非線性模擬電路軟故障診斷[J];系統(tǒng)工程與電子技術(shù);2008年02期

6 胡梅;王紅;胡庚;楊士元;;Soft Fault Diagnosis for Analog Circuits Based on Slope Fault Feature and BP Neural Networks[J];Tsinghua Science and Technology;2007年S1期

，

本文編號(hào)：1877194