Digital Signal Processing technology has transformed our way of life. It has become a fundamental building block in the biomedical, automotive, aerospace, communications and entertainment industries just to mention a few. Ironically, while these systems require interfacing with real world signals, operate in real-time and dynamically interact and present useful information, the pedagogical methods are largely simulation based, off-line processing and static. This paper presents LabVIEW as an educational DSP platform that allows professors to teach and students to learn DSP and advanced concepts by interfacing hardware to live signals, leverage graphical data flow (block diagram) programming to develop and encapsulate signal processing concepts and engage students to interact and develop DSP-based systems by abstracting inherent complexities of low level programming without restricting them. Successful academic case studies of LabVIEW as a DSP platform for real-time FPGA audio processing and multimedia communications are presented.

Interactive software demonstrations and computer-based exercises are often applied in signal processing education to examine concepts such as complex numbers, signal representation, sampling theory, and digital filter specification. While engineering software development environments such as National Instruments LabVIEW simplify the creation of such software, it's clear that some do a better job of improving understanding, motivating learners, and connecting theory with practical concerns. This paper explores how design choices that consider the interactive experience of the learner can have a clear role in determining the success for a demo in meeting these goals. We examine several demonstrations created by the authors, considering the development process and looking at some of the design and implementation choices intended to enhance learning.

We present an Active Noise Control (ANC) system that is designed to cancel acoustic noise at high sound levels. The ANC system is graphically designed using LabVIEW and implemented on FPGA. NLMS algorithm is used for updating the filter co-efficients. The ANC system is evaluated on a realistic test-bed mimicking an actual fMRI bore. The algorithm is tested for various tonal frequencies in the range from 100 to 5000 Hz and the performance is measured in terms of the noise cancellation. We observe that good noise cancellation (15 to 45 dB SPL) can be obtained with NLMS algorithm over the entire bandwidth.