智能信息处理技术

         《智能信息处理技术》课程介绍

智能信息处理就是模拟人或者自然界其他生物处理信息的行为,建立处理复杂系统信息的理论、算法和系统的方法和技术。智能信息处理是当前科学技术发展中的前沿学科,同时也是新思想、新观念、新理论、新技术不断出现并迅速发展的新兴学科,具有非常广泛的应用领域。

《智能信息处理技术》课程是物联网工程专业的选修课。开设本课程的目的是使学生掌握智能信息处理的基本概念、基本原理、基本计算方法;培养学生分析、解决问题的能力,为日后从事工程技术工作、科学研究以及开拓新技术领域,打下坚实的基础。

本课程主要内容包括:智能信息处理基本概念和基本方法,多传感器数据融合的基本原理,分布式自适应动态数据融合方法,神经网络信息处理技术的基本方法,模糊推理系统的基本原理,模糊控制系统设计及应用,协同进化遗传算法,蚁群智能算法等。

本课程第四学年第一学期开设,计划学时32,先修课为:离散数学,数据结构,算法设计与分析,模糊数学。本课程含16学时的实验课程。

 

 

Introduction to the CourseIntelligent Information Processing Technique

 

     Intelligent information processing stimulates behavior of human or other creatures in natural world, constructs the principles and algorithms as well as systemic techniques to process information of complex systems. Intelligent information processing is a front line subject in modern sciences. Meanwhile, it is a quickly developing new subject with the advent of new ideas and new theory along with new techniques. It has been widely used in many fields.

The course “Intelligent Information Processing Technique” is an optional course for students who are majoring in The Internet of Things. The course aims at teaching students to grasp basic concepts, basic principles and basic methods in intelligent information processing, as well as the abilities to analyze and solve practical problems. In order to lay solid foundation for future work such as engineering design, science research as well as exploiting new technique fields.

The main content of the course includes basic concepts and methods of intelligent information processing, basic principles of multi-sensor fusion systems, distributed adaptive dynamic data fusion methods, basic methods of neural network information processing, basic theories of fuzzy inference systems, co-genetic algorithms, ant colony algorithms and so on.

The course will be taught in the first semester of the forth academic year, which includes 32 hours. Its prerequisite courses include discreet mathematics, data structure, algorithm analysis and design, fuzzy mathematics. There are 16 hour experiments in this course.

 

 

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