Nyatega, Charles Okanda and Adegoke, Ogunlade Michael (2014) Determination of Good and Bad Signal in a Given Random Signals Using MATLAB. International Journal of Science and Research (IJSR), 3 (10). pp. 1-4. ISSN Online: 2319-7064
Text
MICHAEL1.pdf - Published Version Download (973kB) |
Abstract
In this modern world we are surrounded by all kinds of signals in various forms. Some of the signals are natural, but most of the signals are manmade. Some signals are necessary (speech), some are pleasant (music), while many are unwanted or unnecessary in a given situation. Therefore extracting or enhancing the useful information from a mix of conflicting information is the simplest form of signal processing [1]. Signal processing is so wide and very interesting in solving many engineering problems, in this paper we used it in bad and good signal detection where by the different samples of signals (sound wave) were provided and from there to select the good ones or bad ones using MATLAB software with the help of Fast Fourier Transform (FFT). Signal analysis procedures have been followed to get the required results by comparing the good known signal s1 and the rest of unknown random signals s2 and s3. Most parameters used in comparison are cross correlation factor and the magnitude of the given signal samples. In the final part we will be able to see the resulting waves using MATLAB showing both magnitude and cross correlation.
Item Type: | Article |
---|---|
Uncontrolled Keywords: | MATLAB, Signal, Correlation, Magnitude, FFT |
Subjects: | T Technology > TK Electrical engineering. Electronics Nuclear engineering Z Bibliography. Library Science. Information Resources > ZA Information resources > ZA4050 Electronic information resources |
Divisions: | Faculty of Engineering, Science and Mathematics > School of Electronics and Computer Science |
Depositing User: | Mrs Oluwafunmilola Bankole |
Date Deposited: | 01 May 2020 11:08 |
Last Modified: | 01 May 2020 11:08 |
URI: | http://eprints.abuad.edu.ng/id/eprint/750 |
Actions (login required)
View Item |