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STM32寄存器手册

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STM32寄存器手册: STM32F101xx、STM32F102xx、STM32F103xx、STM32F105xx和STM32F107xx——先进的基于ARM核心的32位微控制器 .pdf目录STM32F10XXX参考于册5.3BKP功能描述3853.1侵入检测38532RTC校准3954BKP寄存器描述39541备份数据寄存器X( BKP DRX)(X=1…10)39542RTC时钟校准寄存器( BKP RTCCR)39543备份控制寄存器( BKP CR40544备份控制/状态寄存器( KP CSR40545BKP寄存器映像426复位和时钟控制(RCC)4561复位456.1.1系统复位4561.2电源复位4561.3备份域复位4662时钟4662.1HSE时钟4862.2HS时钟4862.3PLL496.24LSE时钟49625LS|时钟49626系统时钟( SYSCLK)选择50627时钟安全系统(CSS)50628RTC时钟5062.9看门狗时钟5062.10时钟输出506.3RCC寄存器描述631时钟控制寄存器(RCC_CR)632时钟配置寄存器(RCC_CFGR)52633时钟中断寄存器(RCC_CR)634APB2外设复位寄存器( RCC APB2RSTR46635APB1外设复位寄存器(RcC_APB1RSTR58636AHB外设时钟使能寄存器( RCC AHBENR)637APB2外设时钟使能寄存器( RCC APB2ENR)66638APB1外设时钟使能寄存器( RCC APB1ENR62639备份域控制寄存器( RCC BDCR)656310控制/状态寄存器( RCC CSR)666311RCC寄存器地址映像687通用和复用功能O(GPO和AF|O)6971GPO功能揹述6971.1通用O(GP|O)70712单独的位设置或位清除71713外部中断/唤醒线717.14复用功能(AF)717.1.5软件重新映射l/O复用功能717.1.6GP|O锁定机制7171.7输入配置717.1.8输出配置727.1.9复用功能配置737.1.10模拟输入配置733/524参照2008年12月RM0008 Reference Manua|英文第7版本译文仅供参考,如有翻译错误,请以英文原稿为准。请读者随时注意在ST网站下载更新版本目录STM32F10XXX参考于册7.2GPO寄存器描述757.2.1端口配置低寄存器(GP| OX CRL)(X=A.E)757.22端口配置高寄存器( GPIOX CRH)(X=A.E757.2.3端凵输入数据寄存器(GP|Ox|DR)(X=A.E)76724端口输出数据寄存器(GP|Ox_ODR)(x=A.E767.2.5端口位设胃/清除寄存器(GP|OⅹBSRR)(x=A.E777.26端冂位清除奇仔器( GPIOX BRR)(x=A.E)777.27端口配置锁定寄存器(GPOx_LCKR)(x=AE)777.3复用功能O和调试配置(AF|O)7873.1把OSC32NOSC320UT作为GPO端口PC14/PC1578732把OSC| NOSC OUT引作为GPO端凵 PDO/PD17873.3CAN复用功能重映射79734JTAG/SWD复用功能重映射797.3.5ADC复用功能重映射807.36定时器复用功能重映射807.3.7 USART复用功能重映射738P2C1复用功能重映射827.3.9SPl1复用功能重映射8274AF|O寄存器描述837.4.1事件控制寄存器( AFIO EVCR837.42复用重映射和调试MO配置奇存器( AFIO MAPR)83743外部中断配置寄存器1(AF| O EXTICR1)86744外韶中断配置寄存器2( AFIO EXTICR2)867.45外部中断配置寄存器3(AFO_ EXTICR3)87746外部中断配置寄存器4(AF| O EXTICR4)877.5GP|O和AF|Q寄存器地址映象888中断和事件898.1套向量中断控制器898.1.1系统嘀嗒( SysTick)校准值寄存器89812中断和异常向量8982外部中断/事件控制器(EXT)8.2.1主要特性91822框图928.23唤醒事件管理92824功能说明9282.5外部中断/事件线路映像948.3EXT寄存器描述95831中断屏蔽奇存器( EXTI IMR)95832事作屏蔽寄存器( EXTI EMR)95833上升沿触发选择寄存器( EXTI RTSR)968.34降沿蝕发选择寄存器( EXTI FTSR)96835软件中断事件寄存器( EXTI SWIER)97836挂起寄存器( EXTI PR)978.37外部中断/事件寄存器映像9DMA控制器(DMA999.1DMA简介9992DMA主要特性999.3功能描述1004/524参照2008年12月RM0008 Reference Manua|英文第7版本译文仅供参考,如有翻译错误,请以英文原稿为准。请读者随时注意在ST网站下载更新版本目录STM32F10XXX参考于册9.3.1DMA处理100932仲裁器10093.3DMA通道101934可编程的数据传输宽度,对齐方式和数据大小端102935错误管理103936中断03937DMA请求映像0494DMA寄存器107941DMA中断状态寄存器 DMA SR107942DMA中断标志清除寄存器 DMA FCR)108943DMA通道x配置寄存器( DMA CCRX)(x=1.7)108944DMA通道x传输数量寄存器( DMA CNDTRX)(x=1.7110945DMA通道x外设地址寄存器 DMA CPARX)(x=1.711094.6DMA通道x存储器地址寄存器 DMA CPARX)(X=1.7)110947DMA寄存器映像11110模拟/数字转换(ADC)11310.1ADC介绍11310.2ADC主要特征11310.3ADC功能描述11410.3.1ADC开关控制1151032ADC时钟11510.3.3通道选择10.34单次转换模式11510.35连续转换模式11610.3.6时序图10.3.7模拟看门狗11610.3.8扫描模式11710.39注入通道管理11710.3.10间断模式104校准11910.5数据对齐119106可编程的通道采样时间12010.7外部触发转换120108DMA请求121109双ADC模式12110.91同步注入模式12210.92同步规则模式12310.93快速交替模式12310.94慢速交替模式12410.9.5交替触发模式12410.9.6独立模式12510.9.7混合的规则注入同步模式12510.98混合的同步规则+交替触发模式125109.9混合同步注入+交替模式12610.10温度传感器1261011ADC中断2710.12ADC寄存器描述2810.121ADC状态寄存器(ADc_SR)1285/524参照2008年12月RM0008 Reference Manua|英文第7版本译文仅供参考,如有翻译错误,请以英文原稿为准。请读者随时注意在ST网站下载更新版本目录STM32F10XXX参考于册10.122ADC控制寄存器1(ADC_CR1)12910.123ADC控制寄存器2(ADC_CR213110.124ADC采样时间寄存器1(ADC_SMPR1)13310.125ADC采样时问寄存器2(ADC_SMPR2)13310.12.6ADC注入通道数据偏移寄存器X(ADC_ JOFRX)(X=1.4)13410.127ADC看门狗高阀值寄存器(ADC_HTR13410.128ADC看门狗低阀值寄存器( ADC LRT)13410.129ADC规则序列寄存器1( ADC SQR1)13510.12.10ADC规则序列寄存器2(ADC_SQR2)13510.1211ADC规则序列寄存器3( ADC SQR3)13610.1212ADC注入序列寄存器(ADC_JsQR13610.1213ADC注入数据寄存器ⅹ( ADC JDRX)(x=1.4)13710.1214ADC规则数据寄存器(ADC_DR)13710.1215ADC寄存器地址映像13811数字/模拟转换(DAC)14011.1DAC简介140112DAC主要特征11.3DAC功能描述4111.3.1使能DAC通道14111.32使能DAC输出缓存1411133DAC数据格式4211.34DAC转换142113.5DAC输出电压14311.3.6选择DAC触发14311.3.7DMA请求14411.3.8噪声生成1441139角波生成14514双DAC通道转换14511.4.1无波形生成的独立触发145114.2带相同LFSR生成的独立触发146114.3带不同LFSR生成的独立触发1461144带相同三角波牛成的独立触发146114.5带不同三角波生成的独立触发1461146同时软件启动147114.7不带波形生成的同时触发14711.4.8带相可LFSR生成的同时触发1471149带不同LFSR生成的同吋铀发147114.10带相同三角波生成的同时触发147114.11带不同三角波生成的同时触发148115DAC寄存器1491151DAC控制寄存器DAC_CR)1491152DAC软什触发寄存器 DAC SWTRIGR)1511153DAC通道1的12位右对齐数据保持寄存器(DAC_DHR12R1)1521154DAC通道1的12位左对齐数据保持寄存器 DAC DHR12L1)1521155DAC通道1的8位石对齐数据保持寄存器DAC_DHR8R1)1521156DAC通道2的12位右对齐数据保持寄存器DAC_DHR12R21531157DAC通道2的12位左对齐数据保持寄存器DAC_DHR12L2)1531158DAC通道2的8位右对齐数据保持寄存器( DAC DHR8R2)1531159双DAC的12位右对齐数据保持寄存器DAC_DHR12RD15411510双DAc的12位左对齐数据保持寄存器DAC_DHR12LD)1546/524参照2008年12月RM0008 Reference Manua|英文第7版本译文仅供参考,如有翻译错误,请以英文原稿为准。请读者随时注意在ST网站下载更新版本目录STM32F10XXX参考于册11511双DAC的8位对齐数据保持寄存器(DAC_DHR8RD)15411512DAC通道1数据输出寄存器( DAC DOR1)15511513DAC通道2数据输出寄存器(DAC_DOR2)15511.514DAC寄存器映像2高级控制定时器(TM和TM8)157121TM1和TM8简介57122TM1和TM8主要特性15712.3TM1和TM8功能描述15812.3.1时基单元1581232计数器模式1601233重复计数器16712.3.4时钟选择1681235捕荻/比较通道17112.3.6输入捕获模式17312.37PWM输入模式174123.8强置输出模式17412.39输出比较模式175123.10PWM模式12.3.11互补输出和死区插入178123.12使用刹车功能179123.13在外部事件时清除 OCXREF信号180123.14产生六步PWM输出181123.15单脉冲模式182123.16编码器接口模式18312.3.17定时器输入异或功能185123.18与霍尔传感器的接口85123.19TMx定时器和外部触发的同步18712320定时器同步19012.3.21调试模式190124TM1和TM8奇存器描述191124.1控制寄存器1( TIMX CR1)1911242挖制寄存器2( TIMX CRI2)192124.3从模式控制寄存器(TMx_SMCR931244DMA中断使能寄仔器( TIMX DIER)951245状态寄存器(TMSR)124.6事件产生寄存器( TIMX EGR)19712.4.7捕获比较模式寄仔器1( TIMX CCMR1)1981248捕获/比较模式寄存器2( TIMX CCMR2)200124.9捕获/比较使能寄存器( TIMX CCER)202124.10计数器( TIMX CNT)203124.11预分频器( TIMX PSO212412自动重装载寄存器( TIMX ARR)20412413重复计数寄存器( TIMX RCR)20412414捕狄/比较寄存器1( TIMX CCR1)205124.15捕获/比较寄存器2( TIMX CCR220512.4.16捕获/比较寄存器3( TIMX CCR3)20512417捕/比较寄存器( TIMX CCR4)20612418刹车和死区寄存器( TIMX BDTR206124.19DMA控制寄存器(TMX_DCR)20812420连续模式的DMA地址( TIMX DMAR)2087/524参照2008年12月RM0008 Reference Manua|英文第7版本译文仅供参考,如有翻译错误,请以英文原稿为准。请读者随时注意在ST网站下载更新版本目录STM32F10XXX参考于册12421TM1和TM8寄存器图13通用定时器(TMX)211131TMx简介211132TMx⊥要功能21113.3TMx功能措述21213.3.1时基单元212133.2计数器模式21313.3.3时钟选择22113.3.4捕获/比较通道223133.5输入捕获模式22513.36PWM输入模式22513.3.7强置输出模式22613.3.8输出比较模式2261339PWM模式227133.10单脉冲模式22913.3.11在外部事件时清除 OCXREF信号231133.12编码器接凵模式231133.13定时器输入异或功能233133.14定时器和外部触发的同步23313.3.15定时器同步235133.16调试模式239134TMx寄存器描述2401341控制寄存器1( TIMX CR1)2401342控制寄存器2( TIMX CR2)241134.3从模式控制寄存器(TMX_SMcR2421344DMA中断使能寄存器( TIMX DIER)2431345状态奇存器( TIMX SR)244134.6事件产生寄存器( TIMX EGR)24513.47捕获/比较模式寄存器1(TMx_cCMR1)2461348捕获/比较模式寄仔器2( TIMX CCMR2)2491349捕获/比较使能寄存器( TIMX CCER251134.10计数器( TIMX CNT252134.11分频器( TIMX PSO25213412自动重装载寄存器( TIMX ARR)25213413捕获/比较寄存器1 TIMX CCR1252134.14捕获/比较寄存器2( TIMX CCR2)25313415捕获/比较寄存器3( TIMX CCR3253134.16捕获/比较寄存器4( TIMX CCR4)253134.17DMA控制寄存器( TIMX DCR)25413.418连续模式的DMA地址( TIMX DMAR)254134.19TMx寄存器图25514基木定时器(TM6和TM7)257141TM6和TM7简介257142TM6和TM7的主要特性257143TM6和TM7的功能25814.3.1时基单元2581432计数模式2591433时钟源26114.34调试模式2628/524参照2008年12月RM0008 Reference Manua|英文第7版本译文仅供参考,如有翻译错误,请以英文原稿为准。请读者随时注意在ST网站下载更新版本目录STM32F10XXX参考于册144TM6和TM7寄存器262144.1控制寄存器1( TIMX CR1)2621442控制寄存器2(TM×CR2)2631443DMA中断使能寄存器(TMxD|ER)2631444状态寄存器( TIMX SE)2641445事件产生寄存器( TIMX EGR)2641446计数器( TIMX CNT2641447预分频器( TIMX PSC)2651448自动重装载寄存器( TIMX ARR)2651449TM6和TIM7寄存器图26615实时时钟(RTC)26715.1RTC简介267152主要特性267153功能描述267153.1概述2671532复位过程2681533读RTC寄存器26815.3.4配置RTC寄存器269153.5RTC标志的设置269154RTC寄存器描述2701541RTC控制寄存器高位(RTC_CRH)2701542RTC控制寄存器低位(RTc_CRL2701543RTC预分频装载寄存器(RTC_ PRLHIRTC PRLL2711544RTC预分频器余数寄存器( RTC DIVH/ RIC DIVL)2721545RTC计数器寄存器(RTC_CNTH/ RTC CNTL)2721546RTC制钟寄存器( RTC ALRH/ RTC ALRL)273154.7RTC寄存器映像2756独立看门狗(WDG)27616.1简介276162WDG主要性能27616.3WDG功能描述276163.1硬件看门狗27616.32寄存器访问保护27616.3.3调试模式276164WDG寄存器描述2771641键寄存器( WDG KR)2771642预分频奇器( WDG PR)2781643重装载寄存器( WDG RLR2781644状态寄存器(WDG_SR)279164.5WDG奇存器映像2797窗口看门狗(WWDG)28017.1WWDG简介28017.2WwDG主要特性28017.3WWDG功能描述28017.4如何编写看门狗超时程序28117.5调试模式28217.6寄存器描述2829/524参照2008年12月RM0008 Reference Manua|英文第7版本译文仅供参考,如有翻译错误,请以英文原稿为准。请读者随时注意在ST网站下载更新版本目录STM32F10XXX参考于册1761控制寄存器( WWDG CR)2821762配置寄存器WWDG_CFR)2831763状态寄存器WWDG_SR)28317.64WWDG寄存器映像2848灵活的静念存储器控制器(FSMC28518.1FSMC功能描述285182框图28518.3AHB接口2868.3.1支持的存储尜和操作286184外部设各地址映像287184.1NOR和 PSRAM地址映像2881842NAND和PC卡地址映像28818.5NOR闪存和 PSRAM控制器289185.1外部存储器接凵信号290185.2支持的存储器及其操作2911853时序规则2911854NOR肉存和 PSRAM时序图2911855同步的成组读30418.56NOR闪存和 PSRAM控制器寄存器308186NAND闪存和PC卡控制器86.1外部存储器接凵信号3131862NAND闪存/PC卡支持的存储器及其操作3141863NAND闪存、ATA和PC卡时序图3141864NAND闪存操作1865NAND闪存预等待功能18.6.6NAND闪存的纠错码ECC计算(NAND闪存)31718.6.7NAND內存和PC卡控制器寄存器317187FSMC寄存器地址映象32419SDO接口(SD|O)325191SDO主要功能325192SD|O总线拓扑32519.3SDO功能描述28193.1sDO适配器3291932SD|OAHB接∏336194卡功能描述194.1卡识别模式3361942卡复位336943操作电压范围确认3371944卡识别过程337194.5写数据块3381946读数据块33819.47数据流操作,数据流写入和数据流读岀(只适用于多媒体卡)338194.8擦除:成组擦除和扇区擦除33919.4.9宽总线选择和解除选择340194.10保护管理340194.11卡状态寄存器342194.12SD状态寄存器344194.13SDMO模式3470/524参照2008年12月RM0008 Reference Manua|英文第7版本译文仅供参考,如有翻译错误,请以英文原稿为准。请读者随时注意在ST网站下载更新版本

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Nonanticipativity2009/8/20page villContents2.4.1Scenario formulation2.4.2Dualization of Nonanticipativity Constraints2.4.3Nonanticipativity duality for general Distributions2.4.4Value of perfect infExercises3 Multistage problems3. 1 Problem Formulation633.1.1The general setting3.1The Linear case653.1.3Scenario trees3.1.4Algebraic Formulation of nonanticipativity constraints 7lDuality....763.2.1Convex multistage problems·763.2.2Optimality Conditions3.2.3Dualization of Feasibility Constraints3.2.4Dualization of nonanticipativity ConstraintsExercises4 Optimization models with Probabilistic Constraints874.1 Introduction874.2 Convexity in Probabilistic Optimization4.2Generalized Concavity of Functions and measures4.2.2Convexity of probabilistically constrained sets1064.2.3Connectedness of Probabilistically Constrained Sets... 113Separable probabilistic Constraints.1144.3Continuity and Differentiability Properties ofDistribution functions4.3.2p-Efficient Points.1154.3.3Optimality Conditions and Duality Theory1224 Optimization Problems with Nonseparable Probabilistic Constraints.. 1324.4Differentiability of Probability Functions and OptimalityConditions13344.2Approximations of Nonseparable ProbabilisticConstraints134.5 Semi-infinite Probabilistic Problems144E1505 Statistical Inference155Statistical Properties of Sample Average Approximation Estimators.. 1555.1.1Consistency of SAA estimators1575.1.2Asymptotics of the saa Optimal value1635.1.3Second order asStochastic Programs5.2 Stoch1745.2.1Consistency of solutions of the SAA GeneralizedEquatio1752009/8/20pContents5.2.2Atotics of saa generalized equations estimators 1775.3 Monte Carlo Sampling Methods180Exponential Rates of Convergence and Sample sizeEstimates in the Case of a finite Feasible se1815.3.2Sample size estimates in the General Case1855.3.3Finite Exponential Convergence1915.4 Quasi-Monte Carlo Methods1935.Variance-Reduction Techniques198Latin hmpling1985.5.2Linear Control random variables method200ng and likelihood ratio methods 205.6 Validation analysis5.6.1Estimation of the optimality g2025.6.2Statistical Testing of Optimality Conditions2075.7Constrained Probler5.7.1Monte Carlo Sampling Approach2105.7.2Validation of an Optimal solution5.8 SAA Method Applied to Multistage Stochastic Programmin205.8.1Statistical Properties of Multistage SAA Estimators22l5.8.2Complexity estimates of Multistage Programs2265.9 Stochastic Approximation Method2305.9Classical Approach5.9.2Robust sA approach..23359.3Mirror Descent sa method235.9.4Accuracy Certificates for Mirror Descent Sa Solutions.. 244Exercis6 Risk Averse Optimi2536.1 Introductio6.2 Mean-Risk models.2546.2.1Main ideas of mean -Risk analysis546.2.2Semideviation6.2.3Weighted Mean Deviations from Quantiles.2566.2.4Average value-at-Risk2576.3 Coherent risk measures2616.3.1Differentiability Properties of Risk Measures2656.3.2Examples of risk Measures..2696.3.3Law invariant risk measures and Stochastic orders2796.3.4Relation to Ambiguous Chance Constraints2856.4 Optimization of risk measures.2886.4.1Dualization of Nonanticipativity Constraints2916.4.2Examples...2956.5 Statistical Properties of Risk measures6.5.IAverage value-at-Ris6.52Absolute semideviation risk measure301Von mises statistical functionals3046.6The problem of moments306中2009/8/20page xContents6.7 Multistage Risk Averse Optimization3086.7.1Scenario tree formulation3086.7.2Conditional risk mappings3156.7.3Risk Averse multistage Stochastic Programming318Exercises3287 Background material3337.1 Optimization and Convex Analysis..334Directional Differentiability3347.1.2Elements of Convex Analysis3367.1.3Optimization and duality3397.1.4Optimality Conditions.............3467.1.5Perturbation analysis3517.1.6Epiconvergence3572 Probability3597.2.1Probability spaces and random variables7.2.2Conditional Probability and Conditional Expectation... 36372.3Measurable multifunctions and random functions3657.2.4Expectation Functions.3687.2.5Uniform Laws of Large Numbers...,,3747.2.6Law of Large Numbers for Random Sets andSubdifferentials3797.2.7Delta method7.2.8Exponential Bounds of the Large Deviations Theory3877.2.9Uniform Exponential Bounds7.3 Elements of Functional analysis3997.3Conjugate duality and differentiability.......... 4017.3.2Lattice structure4034058 Bibliographical remarks407Biibliography415Index4312009/8/20pageList of Notationsequal by definition, 333IR", n-dimensional space, 333A, transpose of matrix(vector)A, 3336I, domain of the conjugate of risk mea-C(X) space of continuous functions, 165sure p, 262CK, polar of cone C, 337Cn, the space of nonempty compact sub-C(v,R"), space of continuously differ-sets of r 379entiable mappings,176set of probability density functions,I Fr influence function. 3042L, orthogonal of (linear) space L, 41Sz, set of contact points, 3990(1), generic constant, 188b(k; a, N), cdf of binomial distribution,Op(), term, 382214S, the set of &-optimal solutions of theo, distance generating function, 236true problem, 18g(x), right-hand-side derivative, 297Va(a), Lebesgue measure of set A C RdCl(A), topological closure of set A, 334195conv(C), convex hull of set C, 337W,(U), space of Lipschitz continuousCorr(X, Y), correlation of X and Y 200functions. 166. 353CoV(X, Y, covariance of X and y, 180[a]+=max{a,0},2ga, weighted mean deviation, 256IA(, indicator function of set A, 334Sc(, support function of set C, 337n(n.f. p). space. 399A(x), set ofdist(x, A), distance from point x to set Ae multipliers vectors334348dom f, domain of function f, 333N(μ,∑), nonmal distribution,16Nc, normal cone to set C, 337dom 9, domain of multifunction 9, 365IR, set of extended real numbers. 333o(z), cdf of standard normal distribution,epif, epigraph of function f, 333IIx, metric projection onto set X, 231epiconvergence, 377convergence in distribution, 163SN, the set of optimal solutions of the0(x,h)d order tangent set 348SAA problem. 156AVOR. Average value-at-Risk. 258Sa, the set of 8-optimal solutions of thef, set of probability measures, 306SAA problem. 181ID(A, B), deviation of set A from set Bn,N, optimal value of the Saa problem,334156IDIZ], dispersion measure of random vari-N(x), sample average function, 155able 7. 2541A(, characteristic function of set A, 334吧, expectation,361int(C), interior of set C, 336TH(A, B), Hausdorff distance between setsLa」, integer part of a∈R,219A and B. 334Isc f, lower semicontinuous hull of funcN, set of positive integers, 359tion f, 3332009/8/20pageList of notationsRc, radial cone to set C, 337C, tangent cone to set C, 337V-f(r), Hessian matrix of second orderpartial derivatives, 179a. subdifferential. 338a, Clarke generalized gradient, 336as, epsilon subdifferential, 380pos w, positive hull of matrix W, 29Pr(A), probability of event A, 360ri relative interior. 337upper semideviation, 255Le, lower semideviation, 255@R. Value-at-Risk. 25Var[X], variance of X, 149, optimal value of the true problem, 1565=(51,……,5), history of the process,{a,b},186r, conjugate of function/, 338f(x, d), generalized directional deriva-g(x, h), directional derivative, 334O,(, term, 382p-efficient point, 116lid, independently identically distributed,1562009/8/20page xlllPrefaceThe main topic of this book is optimization problems involving uncertain parametersfor which stochastic models are available. Although many ways have been proposed tomodel uncertain quantities stochastic models have proved their flexibility and usefulnessin diverse areas of science. This is mainly due to solid mathematical foundations andtheoretical richness of the theory of probabilitystochastic processes, and to soundstatistical techniques of using real dataOptimization problems involving stochastic models occur in almost all areas of scienceand engineering, from telecommunication and medicine to finance This stimulates interestin rigorous ways of formulating, analyzing, and solving such problems. Due to the presenceof random parameters in the model, the theory combines concepts of the optimization theory,the theory of probability and statistics, and functional analysis. Moreover, in recent years thetheory and methods of stochastic programming have undergone major advances. all thesefactors motivated us to present in an accessible and rigorous form contemporary models andideas of stochastic programming. We hope that the book will encourage other researchersto apply stochastic programming models and to undertake further studies of this fascinatinand rapidly developing areaWe do not try to provide a comprehensive presentation of all aspects of stochasticprogramming, but we rather concentrate on theoretical foundations and recent advances inselected areas. The book is organized into seven chapters The first chapter addresses modeling issues. The basic concepts, such as recourse actions, chance(probabilistic)constraintsand the nonanticipativity principle, are introduced in the context of specific models. Thediscussion is aimed at providing motivation for the theoretical developments in the book,rather than practical recommendationsChapters 2 and 3 present detailed development of the theory of two-stage and multistage stochastic programming problems. We analyze properties of the models and developoptimality conditions and duality theory in a rather general setting. Our analysis coversgeneral distributions of uncertain parameters and provides special results for discrete distributions, which are relevant for numerical methods. Due to specific properties of two- andmultistage stochastic programming problems, we were able to derive many of these resultswithout resorting to methods of functional analvsisThe basic assumption in the modeling and technical developments is that the proba-bility distribution of the random data is not influenced by our actions(decisions). In someapplications, this assumption could be unjustified. However, dependence of probability dis-tribution on decisions typically destroys the convex structure of the optimization problemsconsidered, and our analysis exploits convexity in a significant way
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