UCLA Dept. of Electrical Engineering EE 114, Winter 2009 Computer Assignment 4: Linear Predictive Analysis Abstract: This assignment explores the role of linear prediction in spectral analysis for speech. Specifically, this assignment focusses on the effe
UCLA, Electrical Engineering Department EE114, Part 2: Image Processing Solution to Computer assignment #5
Winter Quarter 2009
1. m_files We need to write a couple of m_files. GenerateGaussian.m function h = GenerateGaussian (size, lambda) % this function
EE114, Winter 2009 Computer Assignment 6 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 amplitude FAmp = log10(abs(F)/max(max(abs(F) + 0.000001); % nor
UCLA, Electrical Engineering Department EE 114, Part 2: Image Processing Solution to Computer Assignment #7
Winter Quarter, 2009
1. m_files
Here are several m_files that are used: writeGPJ.m
function result = WriteGPJ(filename, image, quant) % compress an
EE114, Winter 2009 Problem Set 5 Solution _
Problem Set #5 Solution
1) Let f(x,y) be a function below with value 1 in the shaded region and 0 otherwise. f(x,y) y
x
a) Give a sketch of f(x,-y) flip f(x,y) with respect to the x-axis f(x,-y) y
b) Give a sket
EE114, Winter 2009 Problem Set 6 Solution _
Problem Set #6 Solution
1) Let a(m, n ) and b(m, n) be two discrete, aperiodic sequences as specified below. The underscore indicates the location of the origin.
Find the convolution c(m, n ) = a(m, n ) b(m, n )
EE114, Winter 2009 Problem Set 7 Solution _
Problem Set #7 Solution
1) a) Confirm that the four basis vectors of the N = 4 1-D DFT form an orthonormal set, that is, 1, k = l , ak al = 0, otherwise, where, * denotes conjugation. Confirm that the above rela
UCLA Dept. of Electrical Engineering EE 114, Winter 2009 Problem Set 1 - Solutions 1. Let xa (t) be a continuous-time speech signal 50 ms in duration, that is sampled at Fs = 16 kHz. We wish to perform spectral analysis using a radix-2 FFT, with spectral
UCLA Dept. of Electrical Engineering EE 114, Winter 2009 Problem Set 2 Solutions 1. During spectral analysis of speech, a pre-emphasis filter is generally used to boost higher frequencies, since they tend to contain discriminative information. A common fo
UCLA Dept. of Electrical Engineering EE 114, Winter 2009 Problem Set 3 - Solutions 1. Figure 1 represents the spectrum of a steady-state vowel, |X () |. The approximated vocal tract transfer function |H () | is shown as a dashed line.
Figure 1: The spectr
UCLA Dept. of Electrical Engineering EE 114, Winter 2009 Computer Assignment 1: Introduction to Frequency Analysis EE 114 Computer Assignment Report Format: When completing computer assignment reports, we recommend that you start each with an abstract, co
UCLA Dept. of Electrical Engineering EE 114, Winter 2009 Computer Assignment 2: Frequency and Time Analysis of Speech Introduction: The goal of this assignment is to learn the purpose of pre-emphasis filters in speech analysis. Additionally, this assignme
UCLA Dept. of Electrical Engineering EE 114, Winter 2009 Computer Assignment 3: Spectral Analysis of Speech Introduction: This assignment focusses on the relationship between temporal and spectral resolution during speech analysis. Furthermore, the assign
UCLA Dept. of Electrical Engineering EE 114, Winter 2009 Computer Assignment 4: Linear Predictive Analysis Introduction: This assignment explores the role of linear prediction in spectral analysis of speech. Specifically, this assignment focusses on the e
UCLA, Electrical Engineering Department EE 114, Part 2: Image Processing Computer Assignment #6
Winter Quarter, 2009 Assigned: Feb. 18, 2009 Due: Feb. 25, 2009
1. Introduction
In this assignment, you will experiment with the two-dimensional Fourier Transf
UCLA, Electrical Engineering Department EE 114, Part 2: Image Processing Computer Assignment #7
Winter Quarter, 2009 Assigned: February 25, 2009 Due: March 11, 2009
1. Introduction
In this assignment you will implement an image compression algorithm.
2. P
UCLA Dept. of Electrical Engineering EE 114, Winter 2009 Computer Assignment 1 - Solutions Abstract: We consider the analysis of a speech signal in both the time domain and the frequency domain. First we look at the time domain representation of the sente
UCLA Dept. of Electrical Engineering EE 114, Winter 2009 Computer Assignment 3 - Solutions Abstract: This assignment focusses on the relationship between temporal and spectral resolution during speech analysis. The effect of window size during the calcula