UCLA
Dept. of Electrical Engineering
EE 114, Winter 2013
Computer Assignment 1: Introduction to Frequency Analysis
Due: January 16, 2013
EE 114 Computer Assignment Report Format: When completing compu
EE114, Winter 2011
Computer Assignment 5 Solution
_
1 Matlab functions
1.1 ScaleFTAmp.m
function FAmp = ScaleFTAmp(F)
% shift the FT with shift, log, and rescale
c = 4.;
% take the log of the amplitud
UCLA
Dept. of Electrical Engineering
EE 114, Winter 2013
Problem Set 2
Due: January 23, 2013
1. During spectral analysis of speech, a pre-emphasis lter is generally used to boost higher
frequencies, s
UCLA
Dept. of Electrical Engineering
EE 114, Winter 2014
Computer Assignment 6: 2D DFT
Due: February 26, 2014
Introduction: In this assignment, you will experiment with the two-dimensional Fourier Tra
UCLA
Dept. of Electrical Engineering
EE 114, Winter 2013
Computer Assignment 5: Solutions
Matlab code We need to write the following of m-les:
GenerateGaussian.m
function h = GenerateGaussian (size, l
1
Review of Digital Signal Processing Fundamentals
1.1
Discrete-Time Signals
Speech signals occur naturally as continuous-time acoustic signals, xa (t). However, speech signals
1
can be transduced int
UCLA
Dept. of Electrical Engineering
EE 114, Winter 2014
Problem Set 1 - Solutions
1. Consider the discrete time sequence:
x (n) = [4, 1, 2]
(a) Compute the Z-transform X (z ).
Solution:
x (n) z n
X (
UCLA
Dept. of Electrical Engineering
EE 114, Winter 2013
Problem Set 5 Solutions
1. Find the 2D Fourier Transform of the two-dimensional function
f (x, y ) = rect(ax + b) sinc(cy ) .
Answer:
The funct
UCLA
Dept. of Electrical Engineering
EE 114, Winter 2014
Problem Set 4
1. Consider the signal:
x (n) = n for n 0
Using the autocorrelation method of linear prediction analysis, nd the 1st order predic
UCLA
Dept. of Electrical Engineering
EE 114, Winter 2014
Problem Set 5
1. Find the 2D Fourier Transform of the two-dimensional function
f (x, y ) = rect (ax + b) sinc (cy ) .
2. Let f (x, y ) be a fun
UCLA
Dept. of Electrical Engineering
EE 114, Winter 2013
Problem Set 3
Due: January 30, 2013
1. The Fourier Transform can be expressed as:
Xn ej = an ( ) jbn ( ) = |Xn ej |ejn ()
(1)
If x (n) is real,
UCLA
Dept. of Electrical Engineering
EE 114, Winter 2014
Problem Set 6 - Solutions
1. Consider a continuous 2D signal of the form
f (x, y ) = cos (2 (4x + 3y ) .
Suppose you wish to design a sampling/
UCLA
Dept. of Electrical Engineering
EE 114, Winter 2014
Computer Assignment 4: Spectral Analysis of Speech
Due: February 5, 2014
Introduction: This assignment studies the use of time-frequency repres
UCLA
Dept. of Electrical Engineering
EE 114, Winter 2014
Problem Set 7
1. The four basis vectors of the N = 4 1D DFT form an orthonormal set, i.e.,
aH a =
k
where
H
1, k = ,
0, otherwise,
denotes conj
UCLA
Dept. of Electrical Engineering
EE 114, Winter 2014
Problem Set 2 - Solutions
1. During spectral analysis of speech, a pre-emphasis lter is generally used to boost higher
frequencies, since they
UCLA
Dept. of Electrical Engineering
EE 114, Winter 2014
Problem Set 1
1. Figure 1 represents the spectrum of a steady-state vowel, |X e j |. The approximated vocal
tract transfer function |H e j | is
UCLA
Dept. of Electrical Engineering
EE 114, Winter 2014
Problem Set 7 - Solutions
1. The four basis vectors of the N = 4 1D DFT form an orthonormal set, i.e.,
aH a =
k
where
H
1, k = ,
0, otherwise,
UCLA
Dept. of Electrical Engineering
EE 114, Winter 2014
Problem Set 6
1. Consider a continuous 2D signal of the form
f (x, y ) = cos (2 (4x + 3y ) .
Suppose you wish to design a sampling/reconstructi
UCLA
Dept. of Electrical Engineering
EE 114, Winter 2014
Computer Assignment 2 Solutions
Abstract: This assignment explored the eect of pre-emphasis lters on speech lters. Specically,
it studied the e
UCLA
Dept. of Electrical Engineering
EE 114, Winter 2014
Computer Assignment 3: Temporal Analysis of Speech
Due: January 29, 2014
Introduction: This assignment focuses on the temporal analysis of spee
UCLA
Dept. of Electrical Engineering
EE 114, Winter 2014
Computer Assignment 1 - Solutions
Abstract: We consider the analysis of a speech signal in both the time domain and the frequency domain. First
UCLA
Dept. of Electrical Engineering
EE 114, Winter 2013
Computer Assignment 7: Image Enhancement
Due: March 6, 2013
Introduction: In this assignment, you will experiment with image enhancement tools.
1
Review of Digital Signal Processing Fundamentals
1.1
Discrete-Time Signals
Speech signals occur naturally as continuous-time acoustic signals, xa (t). However, speech signals
1
can be transduced int
UCLA
Dept. of Electrical Engineering
EE 114, Winter 2013
Problem Set 7 Solutions
1. The four basis vectors of the N = 4 1D DFT form an orthonormal set, i.e.,
1, k = ,
0, otherwise,
aH a =
k
where
H
de