由北京理工大学研究生院牵头建设的《Probability, Random Process, and Stochastic Geometry in Engineering》慕课，由郭婧副教授主讲与录制。相信这门课程可以帮助研究生深入理解概率理论、随机过程与随机几何的基础和进阶知识，为未来的学术发展和研究打下坚实的基础。
本课程有两个突出的特色：
其一，理论与应用相结合。课程内容涉及与工程应用密切相关的多个主题，如宽平稳随机过程、线性时不变系统、匹配滤波、维纳滤波、无线网络性能分析等。课程不仅讲授随机过程和随机几何的基本理论，还特别注重将这些理论应用于复杂的工程问题，帮助学生掌握有效的分析方法和解决技巧，应对实际工程中的挑战。
其二，知识讲授与课堂实践相结合。课程采用生动活泼的教学方式，并结合信息工程中的实际案例分析、数学建模等活动，通过丰富的课堂练习，帮助学生将理论与实际工程问题有效结合，进一步加深对知识的理解与应用。
通过这门课程，学生将能够掌握必需的研究工具，积累宝贵的实践经验，为在信息、电子等领域的学术和研究事业奠定坚实的基础。
The "Probability, Random Process, and Stochastic Geometry in Engineering" MOOC course, led by the Graduate School of Beijing Institute of Technology and taught by Dr. Jing Guo, is designed to provide a comprehensive understanding of both fundamental and advanced concepts in probability theory, random processes, and stochastic geometry, forming a solid foundation for future academic research and coursework in fields such as information technology and electronics.
This course has two distinctive features:
First, it integrates theory with application. The course covers several topics closely related to engineering applications, such as wide-sense stationary random processes, linear time-invariant systems, matched filtering, Wiener filtering, and wireless network performance analysis. It not only teaches the fundamental theories of random processes and stochastic geometry but also focuses on applying these theories to complex engineering problems, helping students develop effective analytical methods and problem-solving skills to address real-world engineering challenges.
Second, it combines knowledge delivery with hands-on practice. The course adopts an engaging teaching approach and incorporates practical activities such as case studies, mathematical modeling, and exercises from information engineering. Through abundant in-class exercises, students will effectively integrate theory with real engineering problems, deepening their understanding and practical application of the knowledge.
By the end of this course, students will be equipped with the necessary analytical tools and valuable practical experience, laying a strong foundation for their academic and research careers in fields like information technology and electronics.
