přihlášení odhlášení
11MAI
uživatel: anonymní

[Lectures]

Changelog:
2022-09-12 Initial update.

  Lecture date Title
1.

September 19

Self-paced lecture with off-line video:
Introduction. Linear algebra and Matlab review. Polynomials and Taylor series. Euler's identity.
[PDF]

Selected linear algebra resources:

Selected Matlab resources:

Self-paced. Recording of the on-line session from 2020 is here. Recording of the session from 2021 is available here.

2.

September 26

Lecture:
Vector spaces, signals, and images. Signal discretization, quantization and aliasing. Series and Fourier Series. 
[PDF]

Computer session:
Signal discreatization and quantization. Fourier series.
Additional resources: Matlab script, Jupyter/iPython notebook pre-rendered into HTML.

The accompanying video can be downloaded here (in Czech) and here (in English).

3.

October 3

Lecture:
Vector spaces of continuous and discrete waveforms. Discrete Fourier basis and Discrete Fourier Transform. Sampling. Aliasing.
[PDF]

Computer session:
Review of topics from Computer sessions 1 and 2.

-

October 10

Cancelled due to lecturer's illness

4.

October 17

Lecture:
DFT of non-stationary signals. Short-Time Fourier Transform. Windowing and localisation.
Short-Time Fourier Transform. Spectrograms. Time- and frequency resolution.
[PDF]

Computer session:
Application of the DFT. Windowing. Spectrogram.

Test: Can you donwload this video from CTU Sharepoint service?

5.

October 24

Computer session:
Signal processing wrap-up session. The spectrum of a non-stationary signal vs. its spectrogram.

The flute signal for download: [WAV]

[PDF]

-

October 31

Dean's leave

6.

November 7

Lecture:
Data processing review from 11MAMY: linear and logistic regression, regressor selection, regularization, logistic classification, discriminant analysis, principal component analysis, clustering
[PDF]

Computer session:
Statistical data processing review [PDF]
Data archive [ZIP]

Soprano recorder samples for analysis [ZIP]

7.

November 14

Lecture:
Statistical data processing review: Classification.
Bootstrap.
[PDF]

Computer session:
Data archive [ZIP]
Kernel density estimation for Bootstrap confidence intervals: [PDF]

8.

November 21

Lecture:
Principal Components Regression. Partial Least Squares regression.
[PDF]

Computer session:
Data archive [ZIP]

9.

November 28

Lecture:
Introduction to Neural Networks
[PDF]

10.

December 5

Lecture:
Convolutional Neural Networks
MIT lecture slides [PDF] and video [YT]

Computer session:
Data archive [ZIP]

11.

December 12

Lecture:
Recurrent Neural Networks. Long-Short Term Memeory ANNs. Time series prediction.
MIT lecture slides [PDF] and video [YT]

Computer session:
Time series prediction using LSTM ANN.
Data archive [ZIP]

12.

January
9

Project consultations

 

Schoolyear: 2023/2024. Last modified: 12.12.2022 13:17:03. Vzniklo díky podpoře grantu FRVŠ 1344/2007 a grantu FRVŠ 2050/2011.