🤖 AI Summary
This work addresses the lack of effective online experimental platforms in signal processing education and engineering talent development. To bridge this gap, the authors developed and have continuously refined J-DSP, a web-based simulation environment that pioneered the migration of the original Java-based DSP toolkit to an HTML5 architecture, enabling cross-platform— including mobile—accessibility. The platform integrates advanced topics such as digital filter design, FFT-based spectral analysis, machine learning for signal classification, and quantum Fourier transform. Having operated reliably for 25 years, J-DSP has been widely adopted in university courses and National Science Foundation–funded programs, including REU, IRES, and RET initiatives, significantly advancing the modernization of signal processing pedagogy and fostering STEM workforce development.
📝 Abstract
This paper presents the history of the online simulation program Java-DSP (J-DSP) and the most recent function development and deployment. J-DSP was created to support online laboratories in DSP classes and was first deployed in our ASU DSP class in 2000. The development of the program and its extensions was supported by several NSF grants including CCLI and IUSE. The web-based software was developed by our team in Java and later transitioned to the more secure HTML5 environment. J-DSP supports laboratory exercises on: digital filters and their design, the FFT and its utility in spectral analysis, machine learning for signal classification, and more recently online simulations with the Quantum Fourier Transform. Throughout the J-DSP development and deployment of this tool and its associated laboratory exercises, we documented evaluations. Mobile versions of the program for iOS and Android were also developed. J-DSP is used to this day in several universities, and specific functions of the program have been used in NSF REU, IRES and RET workforce development and high school outreach.