LING 490

Spring 2021 All Classes

All Classes

Credit: 3 OR 4 hours.

Course provides an opportunity to focus on various subfields of the linguistic sciences, depending on the interests of the faculty and student.

3 undergraduate hours. 4 graduate hours. May be repeated as topic varies to a maximum of 9 undergraduate hours or 12 graduate hours. Students may register for up to two sections in the same term. Prerequisite: LING 100, LING 400, or consent of instructor.

LING 490 class schedule data for spring 2021
CRN Type Section Time Day Location Instructor Section Details
53661
Online Lab
Online Lecture
YT3
YT3
2:00PM -3:20PM
2:00PM -3:20PM
R
T
n.a.
n.a.
Shi, S
Tang, Y
Shi, S
Tang, Y
Part of Term:
1
Date Range:
01/25/21-05/05/21
Credit:
3 hours
Section Info:
Topic: Fundamentals of Digital Signal Processing. Description: This course aims to give an elementary introduction to concepts, principles and algorithms of digital signal processing. From analogue to digital signals, this course covers digital representations of sound waveforms in both the time and frequency domain, as well as classic methods for signal processing and analysis, such as linear system, discrete Fourier transform, digital filter design and linear prediction. This course focuses on computational implementations of contemporary methodologies in digital signal processing rather than underlying mathematical theories. Therefore, this course requires students to have basic Python, MATLAB or Octave programming skills as prerequisite. This course comprises lectures and laboratory sessions, during which students are expected to produce their own computer code aided by ready-made programs to solve practical problems.
Restriction(s):
Restricted to Undergrad - Urbana-Champaign.
70631
Online Lab
Online Lecture
YT4
YT4
2:00PM -3:20PM
2:00PM -3:20PM
R
T
n.a.
n.a.
Shi, S
Tang, Y
Shi, S
Tang, Y
Part of Term:
1
Date Range:
01/25/21-05/05/21
Credit:
4 hours
Section Info:
Topic: Fundamentals of Digital Signal Processing. Description: This course aims to give an elementary introduction to concepts, principles and algorithms of digital signal processing. From analogue to digital signals, this course covers digital representations of sound waveforms in both the time and frequency domain, as well as classic methods for signal processing and analysis, such as linear system, discrete Fourier transform, digital filter design and linear prediction. This course focuses on computational implementations of contemporary methodologies in digital signal processing rather than underlying mathematical theories. Therefore, this course requires students to have basic Python, MATLAB or Octave programming skills as prerequisite. This course comprises lectures and laboratory sessions, during which students are expected to produce their own computer code aided by ready-made programs to solve practical problems.
Restriction(s):
Restricted to Graduate - Urbana-Champaign.
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