1. SIGNALFILTERING HADJI Isma HAFNAOUI ImaneJune 2012University of MHamed Bouguara - IGEE

2. OUTILINES Introduction Electronic filters 1D Signal Filtering The Butterworth filter The Wiener filter Conclusion 3. Introduction Most of the signals we deal with in real life getcorrupteed in some way or another by someunwanted signals. For the purpose of signal processing andanalysis, it is imperative to get rid of theseinterferences, or at least reduce their effects. This is achieved through applying SignalFiltering techniques. 4. Electronic Filters A Filter is an electronic circuit that removes /attenuates, from a signal, some unwantedcomponent or feature. Filter Application Eliminate background noise Radio tuning to a specific frequency Direct particular frequencies to different speakers Modify digital images Remove specific frequencies in data analysis 5. Filter Characteristics To understand the basics of filtering, it is firstnecessary to learn some important terms used todefine filter characteristics. Cut-Off Frequency (fc): Also referred to as the cornerfrequency, this is the frequency or frequencies that definethe limits of the filter range. Stop Band: The range of frequencies that is filtered out. Pass Band: The range of frequencies which is let throughand recorded. Transition Band: region thatSeparates the passband andstopband. 6. Types of Filters Electronic filters can be: passive or active analog or digital high-pass, low-pass, bandpass, band-reject or all-pass. discrete-time (sampled) or continuous-time Linear or non-linear infinite impulse response (IIR type) or finite impulseresponse (FIR type) Most commercial filters use analog technology. Inother words, these instruments porcess signals(speech or music) in a continuous (analog) patternas they exist in the environment. 7. 1D Filtering 1 D signals can be voltage or current recordings, ecgor eeg signals or else audio signals.Speech signal is one of the most important signals inmultimedia applications. Speech signals degrade due to the presence of noiseand therefore noise reduction is an important field ofspeech processing. We will examine audio filtering in the sense of specificfrequency suppression and extraction.There are many different types of filters available forthe construction of filters. We will specifically use theButterworth filter and the wiener filter and comparetheir action 8. Butterworth Filter A Butterworth filter is a signal processing filterthat has an extremely flat frequency responsein the passband. It is referred to as a maximallyflat magnitude filter and is commonly used inboth analog and digital audio filters. 9. Butterworth Filter We will apply the low pass and high passbutterworth filter to the following noisy speechsignal. 10. Butterworth Filter We design a 3rd order low-pass filter tosuppress high frequencies and apply it to theprevious noisy signal 11. Butterworth Filter We design a 3rd order high-pass filter tosupress low frequencies and apply it to theprevious noisy signal 12. Wiener Filter the Wiener filter is a filter proposed by NorbertWiener during the 1940s Its purpose is to reduce the amountof noise present in a signal by comparison withan estimation of the desired noiseless signal. 13. Wiener Filter We apply the wiener filter on the previous signal with thetrain noise and compare the results. 14. Wiener Filter The filtering effect is better observed in this audiorecording with street/car background noise. 15. Conclusion In this presentation, the concept of signalfiltering was presented where the importanceof filters in signal processing was brought tothe forefront. The butterworth and Wiener Filters weretested on filtering samples of 1D noisy signals. Where Butterworth was able to filter the noiseto a certain degree, Wiener is observed tohave a better noise reduction. 16. THANK YOU