Construction of a Signal-class Experimental Platform Based on Python

There are many advanced concepts and abstractions involved in signal-class courses, which require complex mathematical formulas to be deduced and proven. The derivation process of these formulas is difficult to follow, and there is a challenge in correlating them to the experimental results, making it difficult for students to understand. In response to the non-open-source nature of Matlab, Python, as a free and open-source programming language, has powerful features and rich third-party library resources, supporting various signal processing methods and algorithms, showing unique advantages and effects. Currently, existing experimental simulation platforms for signal courses are often designed for a certain type of course, such as Digital Signal Processing, Communication Principle, Signals and Systems, etc. These platforms only provide limited cases and experiments, and the course content they cover is relatively single and independent, lacking the connection and integration of knowledge points between different courses. To improve this situation, this article chose PyQt5 as the development tool library, with its excellent performance and rich resources, to design and develop an experimental simulation platform for signal-class courses. This platform closely follows the teaching syllabus and divides the platform into multiple modules according to the division of teaching content. Each module contains corresponding course knowledge points and experimental simulations. The platform also has various teaching service functions such as online self-study and teaching guidance, which can help teachers make teaching more vivid and interesting, and can also help students better understand abstract theories and concepts. The platform has been put into teaching and learning in our college and other brotherly universities, which receiving positive feedback and praise from teachers and students.