Example 1: Voltage on a capacitor as a function of time.

Slides:



Advertisements
Similar presentations
Math Review with Matlab:
Advertisements

ECE 8443 – Pattern Recognition EE 3512 – Signals: Continuous and Discrete Objectives: Response to a Sinusoidal Input Frequency Analysis of an RC Circuit.
Han Q Le© ECE 3336 Introduction to Circuits & Electronics Lecture Set #10 Signal Analysis & Processing – Frequency Response & Filters Dr. Han Le ECE Dept.
Ira Fulton School of Engineering Intro to Sinusoids What is a sinusoid? » Mathematical equation : Function of the time variable : Amplitude : Frequency.
EECS 20 Chapter 8 Part 21 Frequency Response Last time we Revisited formal definitions of linearity and time-invariance Found an eigenfunction for linear.
MM3FC Mathematical Modeling 3 LECTURE 1
Lesson 18 Phasors & Complex Numbers in AC
ELECTRIC CIRCUIT ANALYSIS - I
ES250: Electrical Science
1 Prof. Nizamettin AYDIN Digital Signal Processing.
8/27/2015 © 2003, JH McClellan & RW Schafer 1 Signal Processing First Lecture 8 Sampling & Aliasing.
1 Prof. Nizamettin AYDIN Digital Signal Processing.
Motivation Music as a combination of sounds at different frequencies
1 Prof. Nizamettin AYDIN Advanced Digital Signal Processing 30/09/14.
1 Prof. Nizamettin AYDIN Digital Signal Processing.
1 Prof. Nizamettin AYDIN Advanced Digital Signal Processing.
1 Prof. Nizamettin AYDIN Digital Signal Processing.
Lecture 25 Introduction to steady state sinusoidal analysis Overall idea Qualitative example and demonstration System response to complex inputs Complex.
1 Prof. Nizamettin AYDIN Digital Signal Processing.
1 ELECTRICAL CIRCUIT ET 201  Define and explain phasors, time and phasor domain, phasor diagram.  Analyze circuit by using phasors and complex numbers.
1 ECE 3336 Introduction to Circuits & Electronics Note Set #8 Phasors Spring 2013 TUE&TH 5:30-7:00 pm Dr. Wanda Wosik.
Digital Signal Processing
COMPLEX NUMBERS and PHASORS. OBJECTIVES  Use a phasor to represent a sine wave.  Illustrate phase relationships of waveforms using phasors.  Explain.
Lecture 6 (II) COMPLEX NUMBERS and PHASORS. OBJECTIVES A.Use a phasor to represent a sine wave. B.Illustrate phase relationships of waveforms using phasors.
Chapter 2. READING ASSIGNMENTS This Lecture: Chapter 2, pp Appendix A: Complex Numbers Appendix B: MATLAB or Labview Chapter 1: Introduction.
DSP First, 2/e Lecture 11 FIR Filtering Intro. May 2016 © , JH McClellan & RW Schafer 2 License Info for DSPFirst Slides  This work released.
DSP First, 2/e Lecture 7 Fourier Series Analysis.
DSP First, 2/e Lecture 5 Spectrum Representation.
DSP First, 2/e Lecture 6 Periodic Signals, Harmonics & Time-Varying Sinusoids.
DSP-First, 2/e LECTURE #3 Complex Exponentials and Complex Numbers.
DSP First, 2/e LECTURE #1 Sinusoids Aug © , JH McClellan & RW Schafer.
EE301 Phasors, Complex Numbers, And Impedance. Learning Objectives Define a phasor and use phasors to represent sinusoidal voltages and currents Determine.
Lecture 19 Spectrogram: Spectral Analysis via DFT & DTFT
Instructor: Mian Shahzad Iqbal
Lecture 6 Periodic Signals, Harmonics & Time-Varying Sinusoids
Time-Frequency Spectrum
Sinusoidal Excitation of Circuits
Fourier Series Prof. Brian L. Evans
Signal Processing First
COMPLEX NUMBERS and PHASORS
Digital Signal Processing
Lecture 11 FIR Filtering Intro
Periodic Signals Prof. Brian L. Evans
LECTURE #3 Complex Exponentials & Complex Numbers
Signal Processing First
Lecture 12 Linearity & Time-Invariance Convolution
Continuous-Time Signal Analysis
Lecture 5 Spectrum Representation
Sinusoidal Functions, Complex Numbers, and Phasors
Sinusoidal Waveform Phasor Method.
Lecture 14 Digital Filtering of Analog Signals
ECE 1270: Introduction to Electric Circuits
Lecture 10 Digital to Analog (D-to-A) Conversion
Lecture 9 Sampling & Aliasing
Lecture 8 Fourier Series & Spectrum
LECTURE #2 Phase & Time-Shift Delay & Attenuation
Lecture 13 Frequency Response of FIR Filters
Lecture 18 DFS: Discrete Fourier Series, and Windowing
Lecture 17 DFT: Discrete Fourier Transform
Signal Processing First
LECTURE #4 Phasor Addition Theorem
Signal Processing First
Lecture 7C Fourier Series Examples: Common Periodic Signals
Lecture 20 Z Transforms: Introduction
Signal Processing First
Lecture 5A: Operations on the Spectrum
Signal Processing First
Lecture 24 Time-Domain Response for IIR Systems
Lecture 21 Zeros of H(z) and the Frequency Domain
Presentation transcript:

cmpe 362- Signal Processing Instructor: Fatih Alagöz Assistant: Yekta Sait Can

Example 1: Voltage on a capacitor as a function of time. What is Signal? Signal is the variation of a physical phenomenon / quantity with respect to one or more independent variable A signal is a function. Example 1: Voltage on a capacitor as a function of time. RC circuit + -

What is Signal? Example 2: Two different vocoder signals of “Otuz yedi derece” male/female, emotion, background noise, any aspects of vocoder functionallity. Have you had something spicy, salty, sour just before you say it; function of everything !!!

What is Signal? M T W F S Index Example 3 : Closing value of the stock exchange index as a function of days Example 4:Image as a function of x-y coordinates (e.g. 256 X 256 pixel image) M T W F S Index Fig. Stock exchange

What is Signal Processing Process signal(s) for solving many scientific/ engineering/ theoretical purposes The process is includes calculus, Differential equations, Difference equations, Transform theory, Linear time-invariant system theory, System identification and classification, Time-frequency analysis, Spectral estimation, Vector spaces and Linear algebra, Functional analysis, statistical signals and stochastic processes, Detection theory, Estimation theory, Optimization, Numerical methods, Time series, Data mining, etc “The IEEE Transactions on Signal Processing covers novel theory, algorithms, performance analyses and applications of techniques for the processing, understanding, learning, retrieval, mining, and extraction of information from signals. The term "signal" includes, among others, audio, video, speech, image, communication, geophysical, sonar, radar, medical and musical signals. Examples of topics of interest include, but are not limited to, information processing and the theory and application of filtering, coding, transmitting, estimating, detecting, analyzing, recognizing, synthesizing, recording, and reproducing signals” REFERENCE: IEEE Transactions on Signal Processing Journal

Signal Processing everywhere SYSTEM (PROCESS) x(n) or x(t) INPUT SIGNAL y(n) or y(t) OUTPUT SIGNAL Audio, speech, image, video Ranging from nanoscale to deepspace communications Sonar, radar, geosensing Array processing, Control systems (all industry) Seismology, Meteorology, Finance, Health, etc.. IT IS GOOD TO KNOW THIS COURSE

I am currently working on gender classification problem for chicken hatchery eggs DİŞİ FTIR (Fourier Transform Infrared Spectrometer) yöntemi ile allantoik sıvının kimyasal bileşenine (östrojen seviyesi gibi) duyarlı frekans bandındaki (kırmızı bant) ışığın soğurulma oranına dayalı olarak yumurtadaki östrojen miktarı yumurtaya zarar vermeden (uzaktan) saptanabilir. ERKEK

The course in a single slide

ALL ABOUT THREE DOMAINS Z-TRANSFORM-DOMAIN: poles & zeros POLYNOMIALS: H(z) Use H(z) to get Freq. Response FREQ-DOMAIN TIME-DOMAIN 9/12/2018

Lets start from the beginning... Signals…

Signal Processing First LECTURE #1 Sinusoids

READING ASSIGNMENTS This Lecture: Appendix A: Complex Numbers Chapter 2, Sects. 2-1 to 2-5 Appendix A: Complex Numbers Appendix B: MATLAB Chapter 1: Introduction 9/12/2018 2003 rws/jMc

LECTURE OBJECTIVES Write general formula for a “sinusoidal” waveform, or signal From the formula, plot the sinusoid versus time What’s a signal? It’s a function of time, x(t) in the mathematical sense 9/12/2018 2003 rws/jMc

TUNING FORK EXAMPLE CD-ROM demo “A” is at 440 Hertz (Hz) Waveform is a SINUSOIDAL SIGNAL Computer plot looks like a sine wave This should be the mathematical formula: 9/12/2018 2003 rws/jMc

SINUSOID AMPLITUDE EXAMPLES 1-)0.25*sin(2π*300t) 2-)0.50*sin(2π*300t) 3-)1.00*sin(2π*300t) Different Amplitude Sound Examples Amplitude = Asin(2π*300t) Amplitude = 5*Asin(2π*300t) Amplitude =10*A sin(2π*300t) 9/12/2018

SINUSOID FREQUENCY EXAMPLES 1-)1.00sin(2π*300t) 2-)1.00*sin(2π*600t) 3-)1.00*sin(2π*1200t) Different Amplitude Sound Examples Amplitude = 1.00sin(2π*300t) Amplitude = 1.00sin(2π*600t) Amplitude = 1.00sin(2π*1200t) 9/12/2018

SINUSOID PHASE EXAMPLES 1-)1.00sin(2π*300t) 2-)1.00*sin(2π*300t+ π/2) 3-)1.00*sin(2π*300t+ π) 9/12/2018

HUMAN VOICE WITH DIFFERENT SAMPLING FREQUENCIES With the original sampling frequency Fs When sampled with Fs/2 When sampled with 2*Fs When sampled with 5*Fs 9/12/2018

TIME VS FREQUENCY REPRESENTATION OF ONE CLAP RECORD(SPECTROGRAM) 9/12/2018

TIME VS FREQUENCY REPRESENTATION OF TWO CLAPS RECORD (SPECTROGRAM) 9/12/2018

TIME VS FREQUENCY REPRESENTATION OF CLAP + SNAP RECORD (SPECTROGRAM) (FIRST CLAP THEN FINGER SNAP) 9/12/2018

TUNING FORK A-440 Waveform Time (sec) 9/12/2018 2003 rws/jMc

SPEECH EXAMPLE More complicated signal (BAT.WAV) Waveform x(t) is NOT a Sinusoid Theory will tell us x(t) is approximately a sum of sinusoids FOURIER ANALYSIS Break x(t) into its sinusoidal components Called the FREQUENCY SPECTRUM 9/12/2018 2003 rws/jMc

Speech Signal: BAT Nearly Periodic in Vowel Region Period is (Approximately) T = 0.0065 sec 9/12/2018 2003 rws/jMc

DIGITIZE the WAVEFORM x[n] is a SAMPLED SINUSOID A list of numbers stored in memory Sample at 11,025 samples per second Called the SAMPLING RATE of the A/D Time between samples is 1/11025 = 90.7 microsec Output via D/A hardware (at Fsamp) 9/12/2018 2003 rws/jMc

STORING DIGITAL SOUND x[n] is a SAMPLED SINUSOID A list of numbers stored in memory CD rate is 44,100 samples per second 16-bit samples Stereo uses 2 channels Number of bytes for 1 minute is 2 X (16/8) X 60 X 44100 = 10.584 Mbytes 9/12/2018 2003 rws/jMc

SINUSOIDAL SIGNAL FREQUENCY AMPLITUDE PERIOD (in sec) PHASE Radians/sec Hertz (cycles/sec) PERIOD (in sec) AMPLITUDE Magnitude PHASE 9/12/2018 2003 rws/jMc

EXAMPLE of SINUSOID Given the Formula Make a plot 9/12/2018 2003 rws/jMc

PLOT COSINE SIGNAL Formula defines A, w, and f 9/12/2018 2003 rws/jMc

PLOTTING COSINE SIGNAL from the FORMULA Determine period: Determine a peak location by solving Zero crossing is T/4 before or after Positive & Negative peaks spaced by T/2 9/12/2018 2003 rws/jMc

PLOT the SINUSOID Use T=20/3 and the peak location at t=-4 9/12/2018 2003 rws/jMc

PLOTTING COSINE SIGNAL from the FORMULA Determine period: Determine a peak location by solving Peak at t=-4 9/12/2018 © 2003, JH McClellan & RW Schafer

© 2003, JH McClellan & RW Schafer ANSWER for the PLOT Use T=20/3 and the peak location at t=-4 9/12/2018 © 2003, JH McClellan & RW Schafer

© 2003, JH McClellan & RW Schafer TIME-SHIFT In a mathematical formula we can replace t with t-tm Then the t=0 point moves to t=tm Peak value of cos(w(t-tm)) is now at t=tm 9/12/2018 © 2003, JH McClellan & RW Schafer

TIME-SHIFTED SINUSOID 9/12/2018 © 2003, JH McClellan & RW Schafer

PHASE <--> TIME-SHIFT Equate the formulas: and we obtain: or, 9/12/2018 © 2003, JH McClellan & RW Schafer

© 2003, JH McClellan & RW Schafer SINUSOID from a PLOT Measure the period, T Between peaks or zero crossings Compute frequency: w = 2p/T Measure time of a peak: tm Compute phase: f = -w tm Measure height of positive peak: A 3 steps 9/12/2018 © 2003, JH McClellan & RW Schafer

© 2003, JH McClellan & RW Schafer (A, w, f) from a PLOT 9/12/2018 © 2003, JH McClellan & RW Schafer

SINE DRILL (MATLAB GUI) 9/12/2018 © 2003, JH McClellan & RW Schafer

© 2003, JH McClellan & RW Schafer PHASE The cosine signal is periodic Period is 2p Thus adding any multiple of 2p leaves x(t) unchanged 9/12/2018 © 2003, JH McClellan & RW Schafer

© 2003, JH McClellan & RW Schafer COMPLEX NUMBERS To solve: z2 = -1 z = j Math and Physics use z = i Complex number: z = x + j y y z Cartesian coordinate system x 9/12/2018 © 2003, JH McClellan & RW Schafer

© 2003, JH McClellan & RW Schafer PLOT COMPLEX NUMBERS 9/12/2018 © 2003, JH McClellan & RW Schafer

COMPLEX ADDITION = VECTOR Addition 9/12/2018 © 2003, JH McClellan & RW Schafer

© 2003, JH McClellan & RW Schafer *** POLAR FORM *** Vector Form Length =1 Angle = q Common Values j has angle of 0.5p -1 has angle of p - j has angle of 1.5p also, angle of -j could be -0.5p = 1.5p -2p because the PHASE is AMBIGUOUS 9/12/2018 © 2003, JH McClellan & RW Schafer

POLAR <--> RECTANGULAR Relate (x,y) to (r,q) Most calculators do Polar-Rectangular Need a notation for POLAR FORM 9/12/2018 © 2003, JH McClellan & RW Schafer

© 2003, JH McClellan & RW Schafer Euler’s FORMULA Complex Exponential Real part is cosine Imaginary part is sine Magnitude is one 9/12/2018 © 2003, JH McClellan & RW Schafer

© 2003, JH McClellan & RW Schafer COMPLEX EXPONENTIAL Interpret this as a Rotating Vector q = wt Angle changes vs. time ex: w=20p rad/s Rotates 0.2p in 0.01 secs 9/12/2018 © 2003, JH McClellan & RW Schafer

© 2003, JH McClellan & RW Schafer cos = REAL PART Real Part of Euler’s General Sinusoid So, 9/12/2018 © 2003, JH McClellan & RW Schafer

© 2003, JH McClellan & RW Schafer REAL PART EXAMPLE Evaluate: Answer: 9/12/2018 © 2003, JH McClellan & RW Schafer

© 2003, JH McClellan & RW Schafer COMPLEX AMPLITUDE General Sinusoid Complex AMPLITUDE = X Then, any Sinusoid = REAL PART of Xejwt 9/12/2018 © 2003, JH McClellan & RW Schafer

Z DRILL (Complex Arith) 9/12/2018 © 2003, JH McClellan & RW Schafer

© 2003, JH McClellan & RW Schafer AVOID Trigonometry Algebra, even complex, is EASIER !!! Can you recall cos(q1+q2) ? Use: real part of ej(q1+q2) = cos(q1+q2) 9/12/2018 © 2003, JH McClellan & RW Schafer

© 2003, JH McClellan & RW Schafer Euler’s FORMULA Complex Exponential Real part is cosine Imaginary part is sine Magnitude is one 9/12/2018 © 2003, JH McClellan & RW Schafer

Real & Imaginary Part Plots PHASE DIFFERENCE = p/2 9/12/2018 © 2003, JH McClellan & RW Schafer

© 2003, JH McClellan & RW Schafer COMPLEX EXPONENTIAL Interpret this as a Rotating Vector q = wt Angle changes vs. time ex: w=20p rad/s Rotates 0.2p in 0.01 secs 9/12/2018 © 2003, JH McClellan & RW Schafer

© 2003, JH McClellan & RW Schafer Rotating Phasor See Demo on CD-ROM Chapter 2 9/12/2018 © 2003, JH McClellan & RW Schafer

© 2003, JH McClellan & RW Schafer Cos = REAL PART Real Part of Euler’s General Sinusoid So, 9/12/2018 © 2003, JH McClellan & RW Schafer

© 2003, JH McClellan & RW Schafer COMPLEX AMPLITUDE General Sinusoid Sinusoid = REAL PART of (Aejf)ejwt Complex AMPLITUDE = X 9/12/2018 © 2003, JH McClellan & RW Schafer

© 2003, JH McClellan & RW Schafer POP QUIZ: Complex Amp Find the COMPLEX AMPLITUDE for: Use EULER’s FORMULA: 9/12/2018 © 2003, JH McClellan & RW Schafer

© 2003, JH McClellan & RW Schafer WANT to ADD SINUSOIDS ALL SINUSOIDS have SAME FREQUENCY HOW to GET {Amp,Phase} of RESULT ? 9/12/2018 © 2003, JH McClellan & RW Schafer

© 2003, JH McClellan & RW Schafer ADD SINUSOIDS Sum Sinusoid has SAME Frequency 9/12/2018 © 2003, JH McClellan & RW Schafer

© 2003, JH McClellan & RW Schafer PHASOR ADDITION RULE Get the new complex amplitude by complex addition 9/12/2018 © 2003, JH McClellan & RW Schafer

© 2003, JH McClellan & RW Schafer Phasor Addition Proof 9/12/2018 © 2003, JH McClellan & RW Schafer

POP QUIZ: Add Sinusoids ADD THESE 2 SINUSOIDS: COMPLEX ADDITION: 9/12/2018 © 2003, JH McClellan & RW Schafer

© 2003, JH McClellan & RW Schafer POP QUIZ (answer) COMPLEX ADDITION: CONVERT back to cosine form: 9/12/2018 © 2003, JH McClellan & RW Schafer

© 2003, JH McClellan & RW Schafer ADD SINUSOIDS EXAMPLE tm1 tm2 tm3 9/12/2018 © 2003, JH McClellan & RW Schafer

Convert Time-Shift to Phase Measure peak times: tm1=-0.0194, tm2=-0.0556, tm3=-0.0394 Convert to phase (T=0.1) f1=-wtm1 = -2p(tm1 /T) = 70p/180, f2= 200p/180 Amplitudes A1=1.7, A2=1.9, A3=1.532 9/12/2018 © 2003, JH McClellan & RW Schafer

© 2003, JH McClellan & RW Schafer Phasor Add: Numerical Convert Polar to Cartesian X1 = 0.5814 + j1.597 X2 = -1.785 - j0.6498 sum = X3 = -1.204 + j0.9476 Convert back to Polar X3 = 1.532 at angle 141.79p/180 This is the sum 9/12/2018 © 2003, JH McClellan & RW Schafer

© 2003, JH McClellan & RW Schafer ADD SINUSOIDS X1 VECTOR (PHASOR) ADD X3 9/12/2018 X2 © 2003, JH McClellan & RW Schafer