All fields of engineering, whether chemical, civil, electrical, materials, mechanical, etc., encompass a common body of essential mathematics and science. In the freshman year of Drexels E4 program, this common mathematical and scientific foundation is cultivated in the Mathematical and Scientific Foundations of Engineering I, II and III (MSFE I, MSFE II, MSFE III). In an integrated fashion, MSFE I presents the essential calculus, physics and engineering mechanics vital to the freshman engineering student. In the first two quarters, MSFE II presents chemistry with clearly defined engineering applications and significance: in the third quarter, MSFE II presents living systems with the same thrust. Also in the third quarter, MSFE III presents basic circuits and circuit elements, and a brief introduction to electromagnetic theory.
Recent Control Systems, Communication Systems and Digital Signal Processing (DSP) courses have relied heavily on MATLAB and/or C, representing the state of the art in textual programming, for their standard computer tools. Many textbooks are published containing examples, if not sections, utilizing these textual languages. Whereas this environment may be efficient in manipulating equations, textual implementation of processes best described by block diagrams loses its intuitive substance. In this paper, we will describe experiences in a DSP course with an alternative graphical programming environment, namely LabVIEW, from both a student's and an instructor's perspective. We will describe the adjustments that have to be made by individuals trained in conventional, textual programming environments during the transition to the graphical environment. We will give examples of implementations that are better left graphical, such as direct form, canonical, transpose of canonical and cascade realizations of IIR filters. We will conclude with a summary of student feedback on the effectiveness of the graphical programming environment in the presentation of DSP topics.
Most Digital Signal Processing (DSP) courses rely heavily on MATLAB and/or C, representing the state of the art in textual programming, for their standard computer tools. Many textbooks are published containing examples, if not sections, devoted to these textual languages. We have argued, in a previous paper, that whereas this environment may be efficient in manipulating equations, textual implementation of processes best described by block diagrams loses its intuitive substance and gave examples in LabVIEW of implementations that are better left graphical. However, the standard DSP toolkit of LabVIEW is aimed at the practicing engineer/scientist who needs to process acquired data to reach other ends in contrast to a student whose aim is to learn about signal processing. LabVIEW's DSP toolkit is rich with high level algorithms but needs to be enhanced in order to serve the pedagogical needs of students of DSP. Having decided to teach DSP with LabVIEW a year ago, I have found myself writing many routines to complement the standard DSP toolkit as I have tried to demonstrate basic concepts. This paper will describe this additional toolkit that has been growing to make LabVIEW a better teaching tool in a DSP class.
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