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Fir Filters For Technologists, Scientists, And Other Non Ph.D.S

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2009 Annual Conference & Exposition


Austin, Texas

Publication Date

June 14, 2009

Start Date

June 14, 2009

End Date

June 17, 2009



Conference Session

Project-Based Student Learning: Part II

Tagged Division

Engineering Technology

Page Count


Page Numbers

14.632.1 - 14.632.17



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Paper Authors


William Blanton East Tennessee State University

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Dr. Blanton is an associate professor and coordinator of the Biomedical Engineering Technology concentration at East Tennessee State University. His scholarly interests are the applications of digital signal processing to electronic instrumentation, especially medical instrumentation and medical imaging.

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NOTE: The first page of text has been automatically extracted and included below in lieu of an abstract

FIR Filters for Technologists, Scientists, and Other Non-PhDs


The digital filter used most often in digital signal processing (DSP) is the Finite Impulse Response (FIR) filter because it is the easiest to design and it is always stable. An interesting demonstration of the design and implementation of a FIR filter can be shown using MATLAB. The Remez function in MATLAB can be used to generate the filter coefficients for the lowpass, highpass, bandpass, or bandstop filter. MATLAB can be used to generate a set of sinusoidal signals that can be observed in the time domain and frequency domain. The appropriate filter can be applied to pass or block one or all the signals. In addition, MATLAB provides a graphic user interface tool, the Filter Design and Analysis Tool (fdatool), that can be used to generate the filter coefficients. Regardless of the method, the design and implementation of a FIR filter is shown to be straightforward.


Human reality revolves around the analog domain where perception of events is formed by

information that can take on any numeric value at any time. Unfortunately, most modern

information is collected, manipulated, collated, and stored in the digital domain associated with

computers where data must be a discrete value having limited values for specific times only

(Figure 1).

The general scheme for converting from the analog domain to the discrete (digital) domain is

shown in Figure 2. Digital signal processing (DSP) generally consists of an antialiasing filter to

limit the bandwidth of the analog signal, an analog-to-digital converter (ADC) that converts

analog signals to discrete signals that the computer or microcontroller can use, a DSP chip that

manipulates (filters) the digital signal, a digital-to-analog converter (DAC) to convert the digital

Blanton, W. (2009, June), Fir Filters For Technologists, Scientists, And Other Non Ph.D.S Paper presented at 2009 Annual Conference & Exposition, Austin, Texas. 10.18260/1-2--5255

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