ECE 350 Matlab-Based Project #3

Similar documents
Section 8 Convolution and Deconvolution

King Fahd University of Petroleum & Minerals Computer Engineering g Dept

ECE-314 Fall 2012 Review Questions

N! AND THE GAMMA FUNCTION

David Randall. ( )e ikx. k = u x,t. u( x,t)e ikx dx L. x L /2. Recall that the proof of (1) and (2) involves use of the orthogonality condition.

Sampling Example. ( ) δ ( f 1) (1/2)cos(12πt), T 0 = 1

Ideal Amplifier/Attenuator. Memoryless. where k is some real constant. Integrator. System with memory

The Eigen Function of Linear Systems

Solutions to selected problems from the midterm exam Math 222 Winter 2015

In this section we will study periodic signals in terms of their frequency f t is said to be periodic if (4.1)

Manipulations involving the signal amplitude (dependent variable).

6.003: Signals and Systems Lecture 20 April 22, 2010

Big O Notation for Time Complexity of Algorithms

Department of Mathematical and Statistical Sciences University of Alberta

Fourier transform. Continuous-time Fourier transform (CTFT) ω ω

Math 2414 Homework Set 7 Solutions 10 Points

12 Getting Started With Fourier Analysis

Math 6710, Fall 2016 Final Exam Solutions

Pure Math 30: Explained!

Notes 03 largely plagiarized by %khc

1 Notes on Little s Law (l = λw)

L-functions and Class Numbers

2 f(x) dx = 1, 0. 2f(x 1) dx d) 1 4t t6 t. t 2 dt i)

Extremal graph theory II: K t and K t,t

Lecture 15 First Properties of the Brownian Motion

Moment Generating Function

Comparison between Fourier and Corrected Fourier Series Methods

Supplementary Information for Thermal Noises in an Aqueous Quadrupole Micro- and Nano-Trap

If boundary values are necessary, they are called mixed initial-boundary value problems. Again, the simplest prototypes of these IV problems are:

Calculus Limits. Limit of a function.. 1. One-Sided Limits...1. Infinite limits 2. Vertical Asymptotes...3. Calculating Limits Using the Limit Laws.

Week 8 Lecture 3: Problems 49, 50 Fourier analysis Courseware pp (don t look at French very confusing look in the Courseware instead)

6.003 Homework #8 Solutions

SUMMATION OF INFINITE SERIES REVISITED

MAT 271 Project: Partial Fractions for certain rational functions

A Study On (H, 1)(E, q) Product Summability Of Fourier Series And Its Conjugate Series

A TAUBERIAN THEOREM FOR THE WEIGHTED MEAN METHOD OF SUMMABILITY

STK4080/9080 Survival and event history analysis

LIMITS OF FUNCTIONS (I)

ODEs II, Supplement to Lectures 6 & 7: The Jordan Normal Form: Solving Autonomous, Homogeneous Linear Systems. April 2, 2003

Actuarial Society of India

14.02 Principles of Macroeconomics Fall 2005

MATH 507a ASSIGNMENT 4 SOLUTIONS FALL 2018 Prof. Alexander. g (x) dx = g(b) g(0) = g(b),

Linear Time Invariant Systems

Some Properties of Semi-E-Convex Function and Semi-E-Convex Programming*

6.003 Homework #3 Solutions

EE 301 Lab 2 Convolution

th m m m m central moment : E[( X X) ] ( X X) ( x X) f ( x)

Exercise 3 Stochastic Models of Manufacturing Systems 4T400, 6 May

5.74 Introductory Quantum Mechanics II

λiv Av = 0 or ( λi Av ) = 0. In order for a vector v to be an eigenvector, it must be in the kernel of λi

EE 4314 Lab 2 Handout for Workbench #2 Modeling and Identification of the Double-Disk-Torsion-Spring System Fall

6.003: Signals and Systems

Using Linnik's Identity to Approximate the Prime Counting Function with the Logarithmic Integral

ME 452 Fourier Series and Fourier Transform

BEST LINEAR FORECASTS VS. BEST POSSIBLE FORECASTS

FIXED FUZZY POINT THEOREMS IN FUZZY METRIC SPACE

The analysis of the method on the one variable function s limit Ke Wu

EE 4314 Lab 2 Handout for Workbench #1 Modeling and Identification of the Double-Mass-Spring-Damper System Fall

The Central Limit Theorem

Fresnel Dragging Explained

Solutions Manual 4.1. nonlinear. 4.2 The Fourier Series is: and the fundamental frequency is ω 2π

1. Solve by the method of undetermined coefficients and by the method of variation of parameters. (4)

COMM 602: Digital Signal Processing

MCR3U FINAL EXAM REVIEW (JANUARY 2015)

An interesting result about subset sums. Nitu Kitchloo. Lior Pachter. November 27, Abstract

f x x c x c x c... x c...

K3 p K2 p Kp 0 p 2 p 3 p

Problem Set #1. i z. the complex propagation constant. For the characteristic impedance:

Hadamard matrices from the Multiplication Table of the Finite Fields

Principles of Communications Lecture 1: Signals and Systems. Chih-Wei Liu 劉志尉 National Chiao Tung University

Review Answers for E&CE 700T02

NEWTON S SECOND LAW OF MOTION

COS 522: Complexity Theory : Boaz Barak Handout 10: Parallel Repetition Lemma

Review Exercises for Chapter 9

Fermat Numbers in Multinomial Coefficients

Solutions - Homework # 1

SCORE. Exam 2. MA 114 Exam 2 Fall 2017

S n. = n. Sum of first n terms of an A. P is

6.003: Signal Processing Lecture 2a September 11, 2018

Constructing Musical Scales Espen Slettnes

EXISTENCE THEORY OF RANDOM DIFFERENTIAL EQUATIONS D. S. Palimkar

CLOSED FORM EVALUATION OF RESTRICTED SUMS CONTAINING SQUARES OF FIBONOMIAL COEFFICIENTS

F D D D D F. smoothed value of the data including Y t the most recent data.

Transform Techniques

1.3 Convergence Theorems of Fourier Series. k k k k. N N k 1. With this in mind, we state (without proof) the convergence of Fourier series.

Processamento Digital de Sinal

( A) ( B) ( C) ( D) ( E)

The universal vector. Open Access Journal of Mathematical and Theoretical Physics [ ] Introduction [ ] ( 1)

Applying the Moment Generating Functions to the Study of Probability Distributions

BE.430 Tutorial: Linear Operator Theory and Eigenfunction Expansion

Online Supplement to Reactive Tabu Search in a Team-Learning Problem

The equation to any straight line can be expressed in the form:

It is often useful to approximate complicated functions using simpler ones. We consider the task of approximating a function by a polynomial.

Echocardiography Project and Finite Fourier Series

Supplement for SADAGRAD: Strongly Adaptive Stochastic Gradient Methods"

A Note on Prediction with Misspecified Models

Part B: Transform Methods. Professor E. Ambikairajah UNSW, Australia

EGR 544 Communication Theory

Problems and Solutions for Section 3.2 (3.15 through 3.25)

Lecture 9: Polynomial Approximations

Transcription:

ECE 350 Malab-Based Projec #3 Due Dae: Nov. 26, 2008 Read he aached Malab uorial ad read he help files abou fucio i, subs, sem, bar, sum, aa2. he wrie a sigle Malab M file o complee he followig ask for he periodic sigal x () depiced i Figure 1. Submi your M file ad ruig resuls oly. (Noe: please add brief bu clear commes o your M file, ad add ile ad/or leged o your plos if ecessary) Figure 1. Periodic Sigal x () rigoomeric Fourier Series: x( ) a0 = + a cos w0 + b si w0 (a) = 1 Compac rigoomeric Fourier Series: 0 0 = 1 x( ) = c + c cos( w + θ ) (b) Wrie oe M file (by groupig all your Malab commads i oe file ad save i as M file) o do he followig asks: (1) Calculae he coefficies of he rigoomeric Fourier series, a 0, a ad b, where = 1, 2,, 5. (2) Calculae he coefficies of he compac rigoomeric Fourier series, c 0, c ad θ, where = 1, 2,, 5. (Hi: may eed fucio aa2 ad sqr ) (3) Plo he magiude ad phase specra of x() based o he resuls obaied i (2). (4) Deoe by ~ x ( ) he approximaio of x () obaied by summig he firs 6 erms of (icludig he DC erm) of he Fourier series obaied i (a). Plo ~ x ( ) for 0 10π. (5) Plo he origial fucio x () for 0 10π i he same graph of (3) so ha hey ca be compared. (6) Repea (1) o (5) for 31 erms.

MALAB uorial rigoomeric Fourier Series MALAB ca be used o fid ad plo he rigoomeric Fourier series of a periodic fucio. Usig he symbolic mah oolbox, we ca also perform he iegraios ecessary o fid he coefficies a 0, a, ad b i he case of he rigoomeric series. rigoomeric Fourier Series For he periodic waveform show below: f() 4-1 3 6-2 10 he sigal, f() has a period, = 7. hus, w o = 2π/7, ad he Fourier series expasio is: where: f () = a 0 + # a cos! 0 + # b si! 0 =1 =1 a 0 2 # f ()d a # f ()cos! 0 d b # f ()si! 0 d Usig MALAB we ca fid hese coefficies as follows: >> syms >> a0=(1/7)*(i(4,,-1,3)+i(-2,,3,6)) >> a=(2/7)*(i(4*cos(*2*pi*/7),,-1,3)+ i(-2*cos(*2*pi*/7),,3,6)) >> b=(2/7)*(i(4*si(*2*pi*/7),,-1,3)+ i(-2*si(*2*pi*/7),,3,6)) We ca plo hese coefficies as a fucio of. We eed wo plos, oe for he a coefficies ad oe for he b coefficies. I his case we will plo he values for 0 20, usig he followig MALAB commads:

>> vals=1:20; >> avals=subs(a,,vals); >> bvals=subs(b,,vals); >> subplo(2,1,1) >> sem([0,vals],[double(a0),avals]) >> subplo(2,1,2) >> sem([0,vals],[0,bvals]) Noe ha we use he sem fucio o plo hese coefficies sice hey are discree values ad o a coiuous fucio. hese commads should resul i he followig pair of plos: A simple approximaio o he waveform f() ca be foud if we iclude he erms from 0 2. I his case: 2 f ()! a 0 + # a cos 0 + # b si 0 =1 2 =1

his approximaio is foud usig he followig MALAB commads: >> vals=1:2; >> fapprox=double(a0)+sum(subs(a*cos(2**pi*/7),,vals))+ sum(subs(b*si(2**pi*/7),,vals)) ad he ploed alog wih he origial fucio usig: >> vals=-1:.01:6; >> fapproxvals=subs(fapprox,,vals); >> fexac=[4*oes(1,401),-2*oes(1,300)]; >> plo(vals,fapproxvals,vals,fexac) his resuls i he followig plo: We ca see ha he Fourier series expasio does approximae he fucio, however, he approximaio is o very good. We ca improve he approximaio by icludig a greaer umber of erms. If we repea he MALAB commads give above for 0 20:

>> vals=1:20; >> fapprox=double(a0)+sum(subs(a*cos(2**pi*/7),,vals))+ sum(subs(b*si(2**pi*/7),,vals)) >> fapproxvals=subs(fapprox,,vals); >> plo(vals,fapproxvals,vals,fexac) which resuls i: