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Computerized Tools In Digital Signal Processing

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1996 Annual Conference


Washington, District of Columbia

Publication Date

June 23, 1996

Start Date

June 23, 1996

End Date

June 26, 1996



Page Count


Page Numbers

1.115.1 - 1.115.4



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S. Hossein Mousavinezhad

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1532 Computerized Tools in Digital Signal Processing

S. Hossein Mousavinezhad Professor and Chairman Department of Electrical and Computer Engineering Western Michigan University Kalamazoo, MI 49008

INTRODUCTION Digital Signal Processing (DSP) is an important and growing area in electrical/computer engineering with applications in electronics, communication/control systems and biomedical instrumentation. The author has taught undergraduate and graduate courses in DSP where students usually have difficulty understanding and visualizing such abstract concepts as spectrum, impulse response, convolution and difference equations. The subject of DSP is a highly mathematical one which is based on the student prior work in engineering mathematics, electric circuits, linear systems, microprocessors, probability and random processes. The availability of computerized tools and software packages has given the engineering educators a flexibility in covering principles and fundamentals of the subject matter and, at the same time, illustrate the difficult concepts by means of numerical examples and high resolution graphics. We will concentrate on the use of MATHCAD and MATLAB in this paper, although other packages such as MATHEMATICAL and LABVIEW can also be used in certain cases. THE COURSE The DSP course topics include: (see text reference, [1]) A description of digital (discrete-time) signals and systems The sampling process (A/D, D/A), quantization and coding Convolution/correlation functions and difference equation modeling Analysis of linear time-invariant systems in the z-domain Frequency analysis of discrete-time signals and systems The discrete Fourier transform (DFT) and FFT algorithm Implementation issues, structures for realization of DT systems Digital filter design methods, FIR and IIR filter design strategies Quantization of filter coefficients and roundoff effects Optimal filtering in the presence of noise Our students take the DSP course in their senior year after completing courses in linear systems and probability/random processes. The problem is that they may not be very familiar with classical methods of analog filter design (a very detailed and matured subject in electrical engineering) and this is a place where tools like MATLAB and MATHCAD can be very useful and allow students to experiment with different filter approximations like Butterworth, Chebyshev and elliptic design methods. MATHCAD EXAMPLE With the availability of computer tools, it is important that the students can formulate and define the problem first and also have some understanding of the outcome of the problem and its physical interpretation. In this regard, we have found Mathcad to be a useful tool and students, with the availability of the classroom

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Mousavinezhad, S. H. (1996, June), Computerized Tools In Digital Signal Processing Paper presented at 1996 Annual Conference, Washington, District of Columbia. 10.18260/1-2--5930

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