《模式识别导论》实验教学大纲
课程代码 | 045101151 |
课程名称 | 模式识别导论 |
英文名称 | Introductionto Pattern Recognition |
课程类别 | 选修课 |
课程性质 | 选修 |
学时 | 总学时：40实验：8实习：其他： |
学分 | 2.5 |
开课学期 | 第六学期 |
开课单位 | 计算机科学与工程学院 |
适用专业 | 计算机科学与技术 |
授课语言 | 英语 |
先修课程 | 无 |
毕业要求（专业培养能力） | №1.（工程知识）培养学生熟练掌握英语，掌握扎实的计算机科学与技术专业基本原理、方法和手段等方面的基础知识用于解决复杂工程问题，并通过计算机系统分析、建模和计算等方面的先进方法，为将所学基础知识应用到计算机科学与技术研发和工程实践做好准备。 №2.（问题分析）培养学生能够创造性地利用计算机科学基本原理解决计算机领域遇到的问题。 №3.（设计/开发解决方案）能够设计针对计算机工程复杂问题的解决方案，设计满足特定需求的计算机软硬件系统，并能够在设计环节中体现创新意识，考虑社会、健康、安全、法律、文化以及环境等因素。 №4.（研究）培养学生具备计算机系统相关知识并对计算机工程复杂问题进行研究，具有计算机系统研发基本能力、具备问题分析和建模的能力，具有系统级的认知能力和实践能力，掌握自底向上和自顶向下的问题分析方法。 №5.（使用现代工具）能够针对计算机工程复杂问题，开发、选择与使用恰当的技术、资源、现代工程工具和信息技术工具。 №6.（工程与社会）能够基于计算机工程相关背景知识进行合理分析，评价计算机工程实践中的复杂问题解决方案对社会、健康、安全、法律以及文化的影响，并理解应承担的责任。 №7.（环境和可持续发展）能够理解和评价针对计算机工程复杂问题的工程实践对环境、社会可持续发展的影响。 №8.（职业规范）具有人文社会科学素养、社会责任感，能够在工程实践中理解并遵守工程职业道德和规范，履行责任。 №9.（个人和团队）能够在多学科背景下的团队中承担个体、团队成员以及负责人的角色。 №10.（沟通）能够就计算机工程复杂问题与全球业界同行及社会公众进行有效沟通和交流，包括撰写报告和设计文稿、陈述发言、清晰表达或回应指令。并具备良好的国际视野，能够在跨文化背景下进行沟通和交流。 №11.（项目管理）理解并掌握计算机工程管理原理与经济决策方法，并能在多学科环境中应用。 №12.（终身学习）学生能够胜任研究性工作，可继续深造攻读硕士、博士，并具备终身学习的能力。 |
课程培养学生的能力（教学目标） |
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课程简介 | 模式识别实验教学包括介绍MATLAB编程软件和相关工具箱，编程实现决策森林模型并应用在分类问题，编程实现K均值聚类算法并应用在聚类问题。 |
主要仪器设备与软件 | 电脑，MATLAB |
实验报告 | 英文实验报告应包括问题介绍，方法，实验及分析，和总结4个部分。 |
考核方式 | 对实验报告进行评分 |
教材、实验指导书及教学参考书目 | RichardO. Duda, Peter E. Hart, David G. Stork, “Pattern Classification,Second Edition”, John Wiley & sons, Inc. |
制定人及发布时间 | 吴斯 2019年5月8日 |
《课程名称》实验教学内容与学时分配
实验项目编号 | 实验项目名称 | 实验学时 | 实验内容提要 | 实验类型 | 实验要求 | 每组人数 | 主要仪器设备与软件 |
1 | MATLAB | 2 | 介绍MATLAB软件及相关工具箱 | 演示性 | 必做 | 1 | 电脑，MATLAB |
2 | 分类 | 4 | 编程实现决策森林模型并应用于分类问题 | 验证性 | 必做 | 1 | 电脑，MATLAB |
3 | 聚类 | 2 | 编程实现K均值聚类算法并应用于聚类问题 | 验证性 | 必做 | 1 | 电脑，MATLAB |
………… | ………… | ………… |
“Introductionto Pattern Recognition” Syllabus
CourseCode | |
CourseTitle | Introductionto Pattern Recognition |
CourseCategory | ElectiveCourses |
CourseNature | ElectiveCourse |
ClassHours | 40 |
Credits | 2.5 |
Semester | 6 |
Institute | Schoolof Computer Science and Engineering |
ProgramOriented | ComputerScience and Technology |
TeachingLanguage | English |
Prerequisites | None |
StudentOutcomes (Special Training Ability) | №1.Engineering Knowledge: An ability to apply knowledge of English,solid knowledge of professional basic principles, methods andmeans of computer science and technology for solving complexengineering problems, to well prepare the required knowledgeapplied to the computer science and technology research &development and engineering practice through computer systemsanalysis, modeling and calculation and any other aspects of theadvanced approach. №2.Problem Analysis: An ability to creatively use the basicprinciples of computer science to solve the problems encounteredin the computer field. №3.Design / Development Solutions: An ability to design solutions forcomputer engineering complex problems, to design computer hardwareand software systems that meet with specific requirements, and toembody innovation awareness in the design process and take intoaccount social, health, safety, cultural and environmentalfactors. №4.Research: An ability to develop computer system-related knowledgeand research computer engineering complex issues, to develop thebasic capacity of computer systems research & development,systematic cognitive and practice, master the Bottom-up andtop-down problem analysis methods. №5.Applying Modern Tools: An ability to develop, select and useappropriate technologies, resources, modern engineering tools andinformation technology tools for complex computer engineeringissues. №6.Engineering and Society: An ability to conduct a reasonableanalysis and evaluation of the impact of the solutions of complexproblems in computer engineering practice to the social, health,safety, legal and cultural based on computer engineering relatedbackground knowledge, and understand the obligation of takingresponsibility. №7.Environment and Sustainable Development: An ability to understandand evaluate the impact of solutions of complex engineeringproblems in environmental and societal contexts and demonstrateknowledge of and need for sustainable development. №8.Professional Standards: An understanding of humanity science andsocial responsibility, being able to understand and abide byprofessional ethics and standards responsibly in engineeringpractice. №9.Individual and Teams: An ability to function effectively as anindividual, and as a member or leader in diverse teams and inmulti-disciplinary settings. №10.Communication: An ability to communicate effectively on complexcomputer engineering problems with the engineering community andwith society at large, such as being able to comprehend and writeeffective reports and design documentation, make effectivepresentations, give and receive clear instructions, andcommunicate in cross-cultural contexts with internationalperspective. №11.Project Management: Demonstrate knowledge and understanding ofcomputer engineering management principles and methods of economicdecision-making, to function in multidisciplinary environments. №12.Lifelong Learning: An ability to be qualified for research workand can continue their studies for master and doctor degrees, andhave the ability for life-long learning. |
TeachingObjectives |
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CourseDescription | Thelaboratory experiments include the introduction to the softwareMATLAB and related toolboxes, implementation of the decisionforest model for classification tasks, and implementation of theK-means clustering algorithm for clustering tasks. |
Instrumentsand Equipments | Computer,MATLAB |
ExperimentReport | Experimentreports should include the following four parts: the introductionto the task, proposed approach, experimental results anddiscussion, and conclusion. |
Assessment | Gradeexperiment reports |
TeachingMaterials and Reference Books | RichardO. Duda, Peter E. Hart, David G. Stork, “Pattern Classification,Second Edition”, John Wiley & sons, Inc. |
Preparedby Whom and When | SiWu May 8, 2019 |
CourseTitle”ExperimentalTeaching Arrangements
No. | ExperimentItem | ClassHours | ContentSummary | Category | Requirements | Numberof StudentsEach Group | Instruments,Equipments and Software |
1 | MATLAB | 2 | Introducethe software MATLAB and related toolboxes. | Demonstration | Compulsory | 1 | Computer,MATLAB |
2 | Classification | 4 | Implementthe decision forest model and apply it to a classification task. | Verification | Compulsory | 1 | Computer,MATLAB |
3 | Clustering | 2 | Implementthe K-means clustering algorithm and apply it to a clusteringtask. | Verification | Compulsory | 1 | Computer,MATLAB |
…… | …… |
