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Real Time Noise Reduction Using The Tms320 C31 Digital Signal Processing Starter Kit

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Conference

2000 Annual Conference

Location

St. Louis, Missouri

Publication Date

June 18, 2000

Start Date

June 18, 2000

End Date

June 21, 2000

ISSN

2153-5965

Page Count

8

Page Numbers

5.519.1 - 5.519.8

Permanent URL

https://peer.asee.org/8656

Download Count

142

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Paper Authors

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Jianxin Tang

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

Session:1432 Real-Time Noise Reduction Using the TMS320C31 Digital Signal Processing Starter Kit

Jianxin Tang Division of Electrical Engineering Alfred University Alfred, NY 14802 Email: ftang@bigvax.alfred.edu

Abstract

This paper addresses real-time noise reduction using the low-cost TMS320C31 digital signal processing starter kit (DSK). Digital filters, including FIR low pass filter, FIR comb filter, and FIR averaging filter, are designed using MATLAB functions to generate coefficients associated with desired filter characteristics. The filter coefficients are then included in assembly language programs that implement these digital filters. A MATLAB program is used to activate a digital filter, and calculate and plot the frequency response of the filter. When the MATLAB program is run, it plots the spectrum of the filter on the PC screen, assembles the filter assembly language program, and loads/runs the resulting executable file on the TMS320C31 to achieve real-time filtering. Sinusoidal, square, and triangular waveform signals corrupted with white noise are used as input signals to test the filters. Results show the improvement of filter outputs as expected, with actual filter outputs matching theoretical calculations.

1. Introduction

One of the most common problems in signal processing is to extract a desired signal from a noisy measured signal 1 . The noise component of the signal depends on the application. For example, it could be (1) a white noise signal, which is typical of the background noise picked up during the measurement process; (2) a periodic interference signal such as the 60 Hz power- frequency pickup; (3) a low-frequency noise signal, such as radar clutter; (4) any other signal-not necessarily measurement noise-that must be separated. The use of digital signal processors (DSPs) has permitted the increasingly stringent performance requirements and fast, efficient, and accurate filtering of the desired signal from the noise. DSPs, such as the TMS320C31 (C31) from Texas Instruments, are currently used for a wide range of applications from controls and communications to speech processing. They continue to be more and more successful because of available low-cost support tools. DSP-based systems can be readily reprogrammed for a different application.

The C31-based $99 DSK includes Texas Instruments’ C31 floating-point digital signal processor, and an analog interface circuit (AIC) chip with A/D and D/A converters, input (anti- aliasing) and output (reconstruction) filters, all on a single chip. It also includes an assembler, a debugger, and many application examples.

Tang, J. (2000, June), Real Time Noise Reduction Using The Tms320 C31 Digital Signal Processing Starter Kit Paper presented at 2000 Annual Conference, St. Louis, Missouri. https://peer.asee.org/8656

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