LECTURE OBJECTIVES
Signal Processing First
INTRODUCE the Z-TRANSFORM
Give Mathematical Definition
Show how the H(z) POLYNOMIAL simplifies
analysis
Lecture 14
Z Transforms: Introduction
CONVOLUTION is
LECTURE OBJECTIVES
Signal Processing First
INTRODUCE FILTERING IDEA
Weighted Average
Running Average
Lecture 10
FIR Filtering Intro
FINITE IMPULSE RESPONSE FILTERS
FIR
FIR
Filters
Show how to compute
LECTURE OBJECTIVES
Signal Processing First
Two Domains: Time & Frequency
Track the spectrum of x[n] thru an FIR
Filter: Sinusoid-IN gives Sinusoid-OUT
UNIFICATION: How does Frequency
Response affect x
LECTURE OBJECTIVES
Signal Processing First
ZEROS and POLES
Relate H(z) to FREQUENCY RESPONSE
H ( e j ) = H ( z ) z =e j
Lecture 15
Zeros of H(z) and the
Frequency Domain
1/15/2004
THREE DOMAINS:
Show
LECTURE OBJECTIVES
Signal Processing First
SECOND-ORDER IIR FILTERS
TWO FEEDBACK TERMS
2
y[n] = a1 y[n 1] + a2 y[n 2] + bk x[ n k ]
Lecture 18
3-Domains for IIR
k =0
H(z) can have COMPLEX POLES & ZERO
ROSE-HULMAN INSTITUTE OF TECHNOLOGY
Department of Electrical and Computer Engineering
ECE 380 Discrete Time Signals and Systems
Sections 01-02
Winter 2015-16
Yong Jin Daniel Kim
Problem Set 6
Due: Jan
ROSE-HULMAN INSTITUTE OF TECHNOLOGY
Department of Electrical and Computer Engineering
ECE 380 Discrete Time Signals and Systems
Sections 01-02
Winter 2015-16
Yong Jin Daniel Kim
Problem Set 7
Due: Feb