A Hybrid Method for Signal Processing Education

Publish Date: Mar 24, 2011 | 2 Ratings | 5.00 out of 5 | Print | Submit your review

Signal processing educators face a variety of challenges. Aside from ensuring that future engineers remain motivated, educators must teach discrete-time math and other abstract concepts that are often difficult to visualize. To meet these challenges, educators are exploring a “hybrid” programming approach with National Instruments LabVIEW 8.20 software to improve concept demonstrations, computer-based exercises, student projects, and other elements of signal processing education.


1. What Is Hybrid Programming?

University of Texas at Dallas Professor Nasser Kehtarnavaz defines hybrid programming as a combination of graphical and textual programming approaches. Dr. Kehtarnavaz and colleagues examined student programming preferences for hybrid programming when implementing a digital signal processing system. According to a presentation titled “Using Hybrid Programming for DSP Lab Courses,” which will be presented as part of the 2007 Texas Instruments Developer Conference education track, students consistently preferred hybrid programming over exclusive use of graphical or textual approaches.


For the evaluation, students implemented signal processing algorithms as part of a senior-level, undergraduate DSP lab design project. The project involved a cochlear implant system, a prosthetic hearing aid device that can restore hearing to profoundly deaf individuals. The system applies signal processing to convert acquired sound into electrical impulses that are used to directly stimulate auditory nerves.


Figure 1. The CIS algorithm implemented for student evaluation applies digital filters to decompose an input audio signal into frequency bands that are used to stimulate appropriate nerves.


Working in NI LabVIEW, the students implemented a continuous interleaved sampling (CIS) algorithm with separate graphical, textual, and combined graphical-textual implementations (see Figure 1). Students worked on the text-based implementations in LabVIEW MathScript, a math-oriented textual programming language that is a built-in element of LabVIEW. MathScript offers an m-file script syntax that is generally compatible with The MathWorks, Inc. MATLAB® software, COMSOL Script software from COMSOL AB, and others.


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2. Students Prefer Hybrid Programming

Five criteria served as a basis for comparing the students’ preferences on graphical, textual, and hybrid approaches (see Table 1). Based on these criteria, the students consistently preferred the hybrid programming approach.


Table 1. Students considered five criteria in comparing graphical, textual, and hybrid (graphical with textual) programming approaches.


The students’ preferences were not surprising; with the hybrid approach, they could combine the two approaches and benefit from the preferred aspects of both. Indeed, the students related that both graphical and textual approaches had virtues. For signal processing design, the graphical approach was more intuitive than text-based programming. The students also preferred graphical programming for its modularity, GUI features, and availability of built-in tools for signal processing. Students preferred the text-based approach for specifying algebraic equations, compact code size, and familiarity.


With LabVIEW, students can work in a single development environment and choose a “best fit” approach, whether graphical, textual, or hybrid. Such flexibility – along with comprehensive built-in signal processing functionality, a simplified GUI, and simplified access to live signals – makes LabVIEW an ideal platform for signal processing education.


Obtain more information about how you can apply LabVIEW to teach signal processing.

This article first appeared in the Q1 2007 issue of Instrumentation Newsletter.

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