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1. Introduction to Fourier Analysis

2. Exploraiton via a change of basis

3. The Discrete Fourier Transform

4. The DFT in practies

Lecture 3 

1. The Short-Time Fourier Transform

2. FFT: history and algorithms

3. Why the DFT is useful: A few examples

Lecture 6 

1. Welcome to the DSP Course

2. Introduction to signal Processing

3. Discrete time signals

4. The complex exponential

5. The Karplus-Strong Algorithm

Lecture 1 

COURSERA

Digital Signal Processing - DSP

ONLINE  course

1. From Euclid to Hilbert

2. Hilbert Space, properties and bases

3. Hilbert Space approximation

Lecture 2

1. Frequency Response

2. Ideal Filters

3. Filter Design - Part 1: A. of ideal filters

Lecture 8 

1. Realizable Filters

2. Implementation of Digital Filters

3. Filter Design - Part 2: Intuitive Filters

Lecture 9 

1. DFT, DFS, DTFT

2. DTFT: intuition and properties

Lecture 4

1. Relationship between tranforms

2. Sinusoidal modulation

Lecture 5

1. Filter Design - Part 3: Design from specs

2. Real-Time Processing

3. Dereverberation and Echo Cancelation

Lecture 10 

1. Introduction 

2. The Continuous-Time Paradigm

3. Interpolation

4. The Space of Bandlimitted Signals

Lecture 11 

1. Sampling and Aliasing: Introduction

2. Sampling and Aliasing

3. D-T Processing and C-T Signals

4. Another Example of Sampled acquisition

Lecture 12 

1. Stochastic signal processing

2. Quantization

3. A/D and D/A convertion

Lecture 13 

1. Image processing

2. Image manipulations

3. Frequency analysis

Lecture 14 

1. Image filtering

2. Image compression

3. The JPEG compression algorithm

Lecture 15 

1. Digital communication systems

2. Controlling the bandwidth

3. Controlling the power

Lecture 16 

1. Modulation and demodulation

2. Receiver design

Lecture 17 

1. The end

2. Research Projects in Our Lab

3. Startups and DSP

4. Acnowledgements

Lecture 18 

1. Linear Filters

2. Filtering by example

3. Filter stability

Lecture 7 
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