Speech Signal 2000 FIGURE 21.3 s These MATLAB statements read and process a speech file clear, clf 8 clear memory and figure window load speech. dat 8 load speech data file 8 specify sampling time detrend(speech); 8 remove mean and linear trend fram speech N B determine the mmber of speech points t=(0:N-1)*r; 8 specify time sigmal in seconds 8 plot speech signal ubplot(2,1,1), plot(t, s),title(' Speech Signal.) xlabel(Time, s'), gria, pause g determine and plot histogram of speech sigmal using 25 bins 各 clf subplot(2, 1,1), hist(s, 25), title(Distributian of Speech Values),grid, pause plot a spectogram of the signal using windows of 256 pts specgram(s, 256, 8000),title( Speech Signal),pause FIGURE 21.4 21.3 Example 2: Filter Design and analysis MATLAB gives us a number of different options for designing both IIR and FIR digital filters. We can design classical IIR filters(Butterworth, Chebyshev type L, Chebyshev type II, and elliptic) that are lowpass, highpass, andpass, or bandstop filters. We can also use other techniques, such as the Yule-Walker technique, to desig IIR filters with arbitrary passbands. Several techniques allow us to design FIR filters using windowed least squares techniques. The Parks-McClellan algorithm uses the Remez exchange algorithm to design filters with c 2000 by CRC Press LLC© 2000 by CRC Press LLC 21.3 Example 2: Filter Design and Analysis MATLAB gives us a number of different options for designing both IIR and FIR digital filters. We can design classical IIR filters (Butterworth, Chebyshev type I, Chebyshev type II, and elliptic) that are lowpass, highpass, bandpass, or bandstop filters. We can also use other techniques, such as the Yule-Walker technique, to design IIR filters with arbitrary passbands. Several techniques allow us to design FIR filters using windowed least squares techniques. The Parks-McClellan algorithm uses the Remez exchange algorithm to design filters with FIGURE 21.3 FIGURE 21.4