Laplace Transform.

Slides:



Advertisements
Similar presentations
Z-Plane Analysis DR. Wajiha Shah. Content Introduction z-Transform Zeros and Poles Region of Convergence Important z-Transform Pairs Inverse z-Transform.
Advertisements

ECON 397 Macroeconometrics Cunningham
Signal Processing in the Discrete Time Domain Microprocessor Applications (MEE4033) Sogang University Department of Mechanical Engineering.
Laplace Transform (1).
Lecture 7: Basis Functions & Fourier Series
Lecture 3 Laplace transform
Properties of continuous Fourier Transforms
Chapter 7 Laplace Transforms. Applications of Laplace Transform notes Easier than solving differential equations –Used to describe system behavior –We.
EE-2027 SaS, L13 1/13 Lecture 13: Inverse Laplace Transform 5 Laplace transform (3 lectures): Laplace transform as Fourier transform with convergence factor.
Lecture 14: Laplace Transform Properties
1 Lavi Shpigelman, Dynamic Systems and control – – Linear Time Invariant systems  definitions,  Laplace transform,  solutions,  stability.
1 Lavi Shpigelman, Dynamic Systems and control – – Linear Time Invariant systems  definitions,  Laplace transform,  solutions,  stability.
Laplace Transform BIOE 4200.
Fourier Series Summary (From Salivahanan et al, 2002)
INTRODUCTION TO LAPLACE TRANSFORM Advanced Circuit Analysis Technique.
CISE315 SaS, L171/16 Lecture 8: Basis Functions & Fourier Series 3. Basis functions: Concept of basis function. Fourier series representation of time functions.
1 Week 5 Linear operators and the Sturm–Liouville theory 1.Complex differential operators 2.Properties of self-adjoint operators 3.Sturm-Liouville theory.
CHAPTER 4 Laplace Transform.
Fourier Series. Introduction Decompose a periodic input signal into primitive periodic components. A periodic sequence T2T3T t f(t)f(t)
CHAPTER 4 Laplace Transform.
Course Outline (Tentative) Fundamental Concepts of Signals and Systems Signals Systems Linear Time-Invariant (LTI) Systems Convolution integral and sum.
1 Lecture 1: February 20, 2007 Topic: 1. Discrete-Time Signals and Systems.
ECE 8443 – Pattern Recognition EE 3512 – Signals: Continuous and Discrete Objectives: Causality Linearity Time Invariance Temporal Models Response to Periodic.
ECE 352 Systems II Manish K. Gupta, PhD Office: Caldwell Lab Home Page:
Chapter 7 The Laplace Transform
Motivation for the Laplace Transform
Leo Lam © Signals and Systems EE235 Leo Lam.
Chapter 2 The z-transform and Fourier Transforms The Z Transform The Inverse of Z Transform The Prosperity of Z Transform System Function System Function.
Digital and Non-Linear Control
Review of DSP.
Lecture 7: Z-Transform Remember the Laplace transform? This is the same thing but for discrete-time signals! Definition: z is a complex variable: imaginary.
Integral Transform Method
The Z-Transform.
CHAPTER 5 Z-Transform. EKT 230.
Transfer Functions.
Linear Constant-coefficient Difference Equations
Signals and Systems, 2/E by Simon Haykin and Barry Van Veen
EKT 119 ELECTRIC CIRCUIT II
Recap: Chapters 1-7: Signals and Systems
The Laplace Transform Prof. Brian L. Evans
Montek Singh Thurs., Feb. 19, :30-4:45 pm, SN115
LAPLACE TRANSFORMS PART-A UNIT-V.
Chapter 2. Fourier Representation of Signals and Systems
UNIT II Analysis of Continuous Time signal
Signal and Systems Chapter 9: Laplace Transform
Signals and Systems EE235 Leo Lam ©
The sampling of continuous-time signals is an important topic
Prof. Vishal P. Jethava EC Dept. SVBIT,Gandhinagar
Research Methods in Acoustics Lecture 9: Laplace Transform and z-Transform Jonas Braasch.
UNIT V Linear Time Invariant Discrete-Time Systems
Mechatronics Engineering
Digital Control Systems Waseem Gulsher
EE-314 Signals and Linear Systems
B.Sc. II Year Mr. Shrimangale G.W.
Fundamentals of Electric Circuits Chapter 15
Fourier Analysis.
EKT 119 ELECTRIC CIRCUIT II
Discrete-Time Signal processing Chapter 3 the Z-transform
Discrete-Time Signal processing Chapter 3 the Z-transform
9.0 Laplace Transform 9.1 General Principles of Laplace Transform
Finite Impulse Response Filters
10.0 Z-Transform 10.1 General Principles of Z-Transform Z-Transform
CHAPTER 4 Laplace Transform. EMT Signal Analysis.
Review of DSP.
Linear Time Invariant systems
Laplace Transforms Important analytical method for solving linear ordinary differential equations. - Application to nonlinear ODEs? Must linearize first.
Laplace Transforms Important analytical method for solving linear ordinary differential equations. - Application to nonlinear ODEs? Must linearize first.
DIGITAL CONTROL SYSTEM WEEK 3 NUMERICAL APPROXIMATION
THE LAPLACE TRANSFORM LEARNING GOALS Definition
Presentation transcript:

Laplace Transform

Forward Laplace Transform Decompose a signal f(t) into complex sinusoids of the form es t where s is complex: s = s + j2pf Forward (bilateral) Laplace transform f(t): complex-valued function of a real variable t F(s): complex-valued function of a complex variable s Bilateral means that the extent of f(t) can be infinite in both the positive t and negative t direction (a.k.a. two-sided)

Inverse (Bilateral) Transform is a contour integral which represents integration over a complex region– recall that s is complex c is a real constant chosen to ensure convergence of the integral Notation F(s) = L{f(t)} variable t implied for L f(t) = L-1{F(s)} variable s implied for L-1

Laplace Transform Properties Linear or nonlinear? Linear operator L F(s) f(t)

Laplace Transform Properties Time-varying or time-invariant? This is an odd question to ask because the output is in a different domain than the input.

Example

Convergence The condition Re{s} > -Re{a} is the region of convergence, which is the region of s for which the Laplace transform integral converges Re{s} = -Re{a} is not allowed (see next slide)

Regions of Convergence What happens to F(s) = 1/(s+a) at s = -a? (1/0) -e-a t u(-t) and e-a t u(t) have same transform function but different regions of convergence Im{s} Re{s} = -Re{a} Re{s} f(t) 1 t f(t) f(t) = e-a t u(t) causal t -1 f(t) = -e- a t u(-t) anti-causal

Review of 0- and 0+ d(t) not defined at t = 0 but has unit area at t = 0 0- refers to an infinitesimally small time before 0 0+ refers to an infinitesimally small time after 0

Unilateral Laplace Transform Forward transform: lower limit of integration is 0- (i.e. just before 0) to avoid ambiguity that may arise if f(t) contains an impulse at origin Unilateral Laplace transform has no ambiguity in inverse transforms because causal inverse is always taken: No need to specify a region of convergence Disadvantage is that it cannot be used to analyze noncausal systems or noncausal inputs

Existence of Laplace Transform As long as e-s t decays at a faster rate than rate f(t) explodes, Laplace transform converges for some M and s0, there exists s0 > s to make the Laplace transform integral finite We cannot always do this, e.g. does not have a Laplace transform

Key Transform Pairs

Key Transform Pairs

Fourier vs. Laplace Transform Pairs Assuming that Re{a} > 0