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Course Catalog 2012-2013
SGN-1158 Introduction to Signal Processing, short version, 3 cr |
Person responsible
Tatiana Efimushkina, Karen Eguiazarian
Lessons
Study type | P1 | P2 | P3 | P4 | Summer | Implementations | Lecture times and places |
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Requirements
Exam
Learning outcomes
Students should know how to sample a signal, how to analyse a signal in time and frequency domains, able to be use convolution, correlation, discrete-time and digital Fourier transforms.
Content
Content | Core content | Complementary knowledge | Specialist knowledge |
1. | 1 Introduction of different signals, analog vs. digital 2 Audio & speech - sampling - ADC and DAC - aliasing examples - filtering - spectrum 3 Image and video processing - aliasing effects - image enhancement - edge detection, etc. 4 Basic tools: impulse response, convolution Fourier transform |
Evaluation criteria for the course
Course is graded according to in-class exercises and exam.
Assessment scale:
Numerical evaluation scale (1-5) will be used on the course
Prerequisite relations (Requires logging in to POP)
Correspondence of content
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More precise information per implementation
Implementation | Description | Methods of instruction | Implementation |