DSP First, 2/e Lecture 6 Periodic Signals, Harmonics & Time-Varying Sinusoids.

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DSP First, 2/e Lecture 6 Periodic Signals, Harmonics & Time-Varying Sinusoids

May 2016 © , JH McClellan & RW Schafer 2 License Info for SPFirst Slides  This work released under a Creative Commons License with the following terms:Creative Commons License  Attribution  The licensor permits others to copy, distribute, display, and perform the work. In return, licensees must give the original authors credit.  Non-Commercial  The licensor permits others to copy, distribute, display, and perform the work. In return, licensees may not use the work for commercial purposes—unless they get the licensor's permission.  Share Alike  The licensor permits others to distribute derivative works only under a license identical to the one that governs the licensor's work.  Full Text of the License Full Text of the License  This (hidden) page should be kept with the presentation

May 2016 © , JH McClellan & RW Schafer 3 READING ASSIGNMENTS  This Lecture:  Chapter 3, Sections 3-2 and 3-3  Chapter 3, Sections 3-7 and 3-8  Next Lecture:  Fourier Series ANALYSIS  Sections 3-4, 3-5 and 3-6

May 2016 © , JH McClellan & RW Schafer 4 LECTURE OBJECTIVES HARMONIC  Signals with HARMONIC Frequencies  Add Sinusoids with f k = kf 0 Second Topic: FREQUENCY can change vs. TIME Introduce Spectrogram Visualization (spectrogram.m) (plotspec.m) Chirps:

Signals Studied So Far May 2016 © , JH McClellan & RW Schafer 5  Sinusoids  Sum of sinusoids of same frequency  General form: (finite) sum of sinusoids Periodic signals In this lecture

May 2016 © , JH McClellan & RW Schafer 6 SPECTRUM DIAGRAM  Recall Complex Amplitude vs. Freq –100–250 f (in Hz)

May 2016 © , JH McClellan & RW Schafer 7 SPECTRUM for PERIODIC ?  Nearly Periodic in the Vowel Region  Period is (Approximately) T = sec

May 2016 © , JH McClellan & RW Schafer 8 Harmonic Signal

May 2016 © , JH McClellan & RW Schafer 9 Define FUNDAMENTAL FREQ Main point: for periodic signals, all spectral lines have frequencies that are integer multiples of the fundamental frequency

May 2016 © , JH McClellan & RW Schafer 10 Harmonic Signal Spectrum

Periodic Signal: Example May 2016 © , JH McClellan & RW Schafer 11 Fundamental frequency

May 2016 © , JH McClellan & RW Schafer 12 What is the fundamental frequency? Harmonic Spectrum (3 Freqs) 3rd 5th 10 Hz

May 2016 © , JH McClellan & RW Schafer 13 POP QUIZ: FUNDAMENTAL  Here’s another spectrum: What is the fundamental frequency? (0.1)GCD(104,240) = (0.1)(8)=0.8 Hz –10.4–24 f (in Hz)

May 2016 © , JH McClellan & RW Schafer 14 SPECIAL RELATIONSHIP to get a PERIODIC SIGNAL IRRATIONAL SPECTRUM NON-PERIODIC SIGNAL

May 2016 © , JH McClellan & RW Schafer 15 Harmonic Signal (3 Freqs) T=0.1 PERIODIC

May 2016 © , JH McClellan & RW Schafer 16 NON-Harmonic Signal NOT PERIODIC

May 2016 © , JH McClellan & RW Schafer 17 FREQUENCY ANALYSIS  Now, a much HARDER problem  Given a recording of a song, have the computer write the music  Can a machine extract frequencies?  Yes, if we COMPUTE the spectrum for x(t)  During short intervals

May 2016 © , JH McClellan & RW Schafer 18 Time-Varying FREQUENCIES Diagram Frequency is the vertical axis Time is the horizontal axis A-440

May 2016 © , JH McClellan & RW Schafer 19 SIMPLE TEST SIGNAL  C-major SCALE: stepped frequencies  Frequency is constant for each note IDEAL

May 2016 © , JH McClellan & RW Schafer 20 SPECTROGRAM  SPECTROGRAM Tool  MATLAB function is spectrogram.m  SP-First has plotspec.m & spectgr.m  ANALYSIS program  Takes x(t) as input  Produces spectrum values X k  Breaks x(t) into SHORT TIME SEGMENTS  Then uses the FFT (Fast Fourier Transform)

May 2016 © , JH McClellan & RW Schafer 21 SPECTROGRAM EXAMPLE  Two Constant Frequencies: Beats

May 2016 © , JH McClellan & RW Schafer 22 AM Radio Signal  Same form as BEAT Notes, but higher in freq

May 2016 © , JH McClellan & RW Schafer 23 SPECTRUM of AM (Amplitude Modulation)  SUM of 4 complex exponentials: What is the fundamental frequency? 648 Hz ?24 Hz ? f (in Hz) –672 –648

May 2016 © , JH McClellan & RW Schafer 24 STEPPED FREQUENCIES  C-major SCALE: successive sinusoids  Frequency is constant for each note IDEAL

May 2016 © , JH McClellan & RW Schafer 25 SPECTROGRAM of C-Scale ARTIFACTS at Transitions Sinusoids ONLY From SPECTROGRAM ANALYSIS PROGRAM

May 2016 © , JH McClellan & RW Schafer 26 Spectrogram of LAB SONG ARTIFACTS at Transitions Sinusoids ONLY Analysis Frame = 40ms

Overlapping Sections in Spectrograms (useful in Labs)  50% overlap is common  Consider edge effects when analyzing a short sinusoid May 2016 © , JH McClellan & RW Schafer 27 SECTION LOCATIONS MIDDLE of SECTION is REFERENCE TIME

May 2016 © , JH McClellan & RW Schafer 28 Spectrogram of BAT (plotspec)

May 2016 © , JH McClellan & RW Schafer 29 Time-Varying Frequency  Frequency can change vs. time  Continuously, not stepped  FREQUENCY MODULATION (FM)  CHIRP SIGNALS  Linear Frequency Modulation (LFM) VOICE

May 2016 © , JH McClellan & RW Schafer 30 New Signal: Linear FM  Called Chirp Signals (LFM)  Quadratic phase  Freq will change LINEARLY vs. time  Example of Frequency Modulation (FM)  Define “instantaneous frequency” QUADRATIC

May 2016 © , JH McClellan & RW Schafer 31 INSTANTANEOUS FREQ  Definition  For Sinusoid: Derivative of the “Angle” Makes sense

May 2016 © , JH McClellan & RW Schafer 32 INSTANTANEOUS FREQ of the Chirp  Chirp Signals have Quadratic phase  Freq will change LINEARLY vs. time

May 2016 © , JH McClellan & RW Schafer 33 CHIRP SPECTROGRAM

May 2016 © , JH McClellan & RW Schafer 34 CHIRP WAVEFORM

May 2016 © , JH McClellan & RW Schafer 35 OTHER CHIRPS   (t) can be anything:   (t) could be speech or music:  FM radio broadcast

May 2016 © , JH McClellan & RW Schafer 36 SINE-WAVE FREQUENCY MODULATION (FM) Look at CD-ROM Demos in Ch 3

May 2016 © , JH McClellan & RW Schafer 37 Problem Solving Skills  Math Formula  Sum of Cosines  Amp, Freq, Phase  Recorded Signals  Speech  Music  No simple formula  Plot & Sketches  S(t) versus t  Spectrum  MATLAB  Numerical  Computation  Plotting list of numbers