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[Coursera] Computational Methods for Data Analysis (University of Washington) (compmethods)

by: University of Washington

Publisher: Academic Torrents

Contributor: Academic Torrents

Academictorrents_collection: video-lectures

Addeddate: 2018-08-12 17:56:22

External-identifier: urn:academictorrents:4281ef52a65d26489e686a0540d86abd4161b88e

Identifier: academictorrents_4281ef52a65d26489e686a0540d86abd4161b88e

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Scanner: Internet Archive Python library 1.8.1

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42 files

HTML

BACK

59.7K

DiscussionForums.html

44.6K

FAQabouttheCourse.html

60.8K

HomeAnnouncements.html

60.8K

zip_page.html

34.8K

Homework.html

48.8K

0_Homework_Fluffy_Dog_Swallowed_a_Marble.html

48.8K

zip_page.html

56.0K

QuickQuestions15.html

126.2K

Quizzes.html

126.4K

0_Week_1_Lecture_1_Quiz.html

69.8K

10_Week_4_Lecture_11_Quiz.html

136.1K

11_Week_5_Lecture_12_Quiz.html

44.4K

12_Week_5_Lecture_13_Quiz.html

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13_Week_5_Lecture_14_Quiz.html

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14_Week_6_Lecture_15_Quiz.html

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15_Week_6_Lecture_16_Quiz.html

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16_Week_7_Lecture_17_Quiz.html

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17_Week_7_Lecture_18_Quiz.html

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18_Week_7_Lecture_19_Quiz.html

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19_Week_8_Lecture_20_Quiz.html

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1_Week_1_Lecture_2_Quiz.html

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20_Week_8_Lecture_21_Quiz.html

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21_Week_8_Lecture_22_Quiz.html

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22_Week_9_Lecture_23_Quiz.html

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23_Week_9_Lecture_24_Quiz.html

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24_Week_9_Lecture_25_Quiz.html

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25_Week_10_Lecture_26_Quiz.html

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26_Week_10_Lecture_27_Quiz.html

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27_Week_10_Lecture_28_Quiz.html

100.8K

2_Week_1_Lecture_3_Quiz.html

103.5K

3_Week_2_Lecture_4_Quiz.html

61.8K

4_Week_2_Lecture_5_Quiz.html

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5_Week_2_Lecture_6_Quiz.html

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6_Week_3_Lecture_7_Quiz.html

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7_Week_3_Lecture_8_Quiz.html

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8_Week_4_Lecture_9_Quiz.html

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9_Week_4_Lecture_10_Quiz.html

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ResourcesfortheCourse.html

44.3K

WelcometotheCourse.html

32.5K

assignment_home.html

60.8K

course_home.html

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entered_login.html

1 file

ITEM TILE

119 files

MPEG4

BACK

15.5M

01_Course_Overview.mp4

57.2M

01_Course_Introduction_9-30.mp4

16.1M

01_Use_of_MATLAB_for_the__course_2-41.mp4

26.4M

01_W01_L01_P01_-_Basics_of_the_Fourier_Transform_10-16.mp4

28.0M

02_W01_L01_P02_-_Representation_of_signals_as_frequencies_10-01.mp4

25.8M

03_W01_L01_P03_-_Implementing_the_FFT_routine_13-24.mp4

16.6M

04_W01_L01_P04_-_Derivatives_with_the_FFT_9-35.mp4

22.9M

01_W01_L02_P01_-_The_FFT_for_Radar_8-13.mp4

23.5M

02_W01_L02_P02_-_Signals_FFT_and_noise_11-22.mp4

15.5M

03_W01_L02_P03_-_White_noise_on_signals_7-35.mp4

20.3M

04_W01_L02_P04_-_Denoising_via_filtering_9-56.mp4

19.9M

05_W01_L02_P05_-_Signal_detection_and_thresholding_7-00.mp4

26.5M

01_W01_L03_P01_-_Averaging_over_white-noise_in_signals_10-33.mp4

26.4M

02_W01_L03_P02_-_Convergence_to_signal_through_repeated_sampling_12-25.mp4

34.8M

03_W01_L03_P03_-_Moving_signals_and_averaging_in_frequency_15-23.mp4

27.7M

04_W01_L03_P04_-_Signal_detection_through_averaging_and_averaging_10-04.mp4

29.6M

01_W2_L4_P1-A_Window_for_Fourier_Transforming_9-35.mp4

29.1M

02_W2_L4_P2-The_Gabor_Transform_10-03.mp4

27.4M

03_W2_L4_P3-Propeties_of_the_Gabor_Transform_9-06.mp4

27.1M

04_W2_L4_P4-Trade-offs_in_time-frequency_representations_9-45.mp4

23.0M

05_W2_L4_P5-Other_short-time_transforms_8-10.mp4

35.0M

01_W2_L5_P1-Introduction_to_Wavelets_12-40.mp4

24.3M

02_W2_L5_P2-The_Haar_wavelet_8-54.mp4

22.7M

03_W2_L5_P3-Some_wavelet_theorems_and_properties_8-59.mp4

21.5M

04_W2_L5_P4-Mexican_Hat_wavelet_8-44.mp4

27.9M

05_W2_L5_P5-More_wavelet_properties_10-19.mp4

29.6M

01_W2_L6_P1-Wavelet_building_blocks-_Dialations_and_Translations_9-17.mp4

29.8M

02_W2_L6_P2-An_analogy-Fourier_Analysis_and_eigenfunction_expansions_9-54.mp4

28.8M

03_W2_L6_P3-The_wavelet_basis_10-06.mp4

24.4M

04_W2_L6_P4-Multi-resolution_analysis_8-53.mp4

18.4M

01_W3_L7_P1-Building_signals_in_MATLAB_10-37.mp4

28.6M

02_W3_L7_P2-The_Gabor_Transform_15-54.mp4

37.5M

03_W3_L7_P3-Spectrograms_16-54.mp4

44.9M

01_W3_L8_P1-Filter_Design_Toolbox_19-59.mp4

60.1M

02_W3_L8_P2-Wavelet_Toolbox_25-05.mp4

32.7M

01_W4_L9_P1-Applications_of_image_processing_12-41.mp4

12.5M

02_W4_L9_P2-MATLAB_and_image_manipulation_7-02.mp4

27.1M

03_W4_L9_P3-Spectrum_of_Images_13-44.mp4

27.6M

01_W4_L10_P1-Image_Properties_10-08.mp4

22.0M

02_W4_L10_P2-Adding_Image_Noise_10-16.mp4

23.1M

03_W4_L10_P3-Basic_Image_Filter_Setup_11-24.mp4

12.3M

04_W4_L10_P4-Gaussian_Data_Filtering_6-48.mp4

27.7M

05_W4_L10_P5-Filter_Design_and_Image_Clean-up_11-26.mp4

29.8M

01_W4_L11_P1-_Filtering_through_diffusion_10-11.mp4

27.2M

02_W4_L11_P2_-_The_1D_Diffusion_Equation_9-22.mp4

29.3M

03_W4_L11_P3_-_Equivalence_of_Diffusion_with_Gaussian_Filtering_10-09.mp4

37.5M

04_W4_L11_P4_-_MATLAB_implementation_of_diffusion_filtering_20-05.mp4

29.7M

01_W5_L12_P1_-_Matrix_manipulations_on_data_10-44.mp4

23.2M

02_W5_L12_P2_-_Basics_of_the_SVD_8-47.mp4

27.0M

03_W5_L12_P3_-_Matrix_Decomposition_9-54.mp4

19.8M

04_W5_L12_P4_-_Properties_of_the_SVD_7-04.mp4

25.9M

05_W5_L12_P5_-_Computing_the_SVD_10-05.mp4

26.7M

01_W5_L13_P1_-_Review_of_SVD_9-55.mp4

32.5M

02_W5_L13_P2_-_Diagonalization_of_Matrices_11-50.mp4

25.4M

03_W5_L13_P3_-_SVD_Diagonalization_9-24.mp4

24.4M

04_W5_L13_P4_-_Theorems_of_the_SVD_9-21.mp4

28.0M

05_W5_L13_P5_-_Low-rank_Reductions_9-19.mp4

54.4M

01_W5_L14_P1_-_A_Spring_Mass_System_16-11.mp4

33.8M

02_W5_L14_P2_-_The_Variance_and_Covariance_of_the_Data_11-56.mp4

26.5M

03_W5_L14_P3_-_Covariance_Matrix_and_Redundancy_9-35.mp4

26.1M

04_W5_L14_P4_-_The_SVD_and_PCA_10-11.mp4

28.2M

01_W6_L15_P1-_Interpreting_the_covariance_matrix-diagonal_elements_9-30.mp4

25.2M

02_W6_L15_P2-Interpreting_the_covariance_matrix-off-diagonals_9-38.mp4

24.3M

03_W6_L15_P3-Relationship_to_eigenvectors-eigenvalues_8-03.mp4

24.0M

04_W6_L15_P4-SVD_versus_EIGS_9-53.mp4

34.5M

05_W6_L15_P5-Interpretation_for_spring-mass_system_11-11.mp4

33.5M

01_W6_L16_P1-Modal_expansions_11-55.mp4

23.4M

02_W6_L16_P2-SVD_for_basis_expansions_10-41.mp4

28.5M

03_W6_L16_P3-Low_rank_reconstructions_of_a_function_15-09.mp4

24.1M

04_W6_L16_P4-Another_low-rank_approximation_13-15.mp4

34.7M

01_W7_L17_P1_-_Independent_Components_-_The_Cocktail_Party_Problem_12-11.mp4

23.2M

02_W7_L17_P2_-_Signal_Separation_8-49.mp4

24.0M

03_W7_L17_P3_-_Separating_Images_9-22.mp4

36.4M

04_W7_L17_P4_-_Mathematical_Framework_and_the_SVD_14-13.mp4

31.6M

01_W7_L18_P1_-_Review_of_Mathematical_Algorithm_10-12.mp4

34.3M

02_W7_L18_P2_-_Computing_the_Principal_Directions_12-38.mp4

24.4M

03_W7_L18_P3_-_Computing_the_Stretching_10-06.mp4

34.2M

04_W7_L18_P4_-_Using_Kurtosis_for_Final_Analysis_10-06.mp4

31.1M

05_W7_L18_P5_-_Combining_all_the_Components_for_ICA_9-01.mp4

28.0M

01_W7_L19_P1_-_Algorithm_Overview_of_ICA_and_Image_Separation_12-47.mp4

16.2M

02_W7_L19_P2_-_Mixing_Images_9-29.mp4

25.3M

03_W7_L19_P3_-_Computing_the_Stretching_and_Rotation_14-30.mp4

32.4M

04_W7_L19_P4_-_Separating_the_Images_15-18.mp4

37.4M

01_W8_L20_P1-Introduction_to_recognition_ideas_14-27.mp4

41.0M

02_W8_L20_P2-Quantifying_image_recognition_13-16.mp4

17.9M

03_W8_L20_P3-Pre-processing_dog_cat_images_9-30.mp4

25.4M

04_W8_L20_P4-wavelet_transforming_dogs_cats_12-05.mp4

24.0M

01_W8_L21_P1-Wavelet_dogs_and_cats_10-18.mp4

32.0M

02_W8_L21_P2-Building_dog_cat_PCA_components_14-40.mp4

20.2M

03_W8_L21_P3-Features_10-54.mp4

26.5M

04_W8_L21_P4-linear_discrimination_9-42.mp4

31.8M

01_W8_L22_P1-Putting_all_the_algorithm_parts_together_11-12.mp4

22.3M

02_W8_L22_P2-Training_sets_10-07.mp4

33.3M

03_W8_L22_P3-The_linear_discriminant_14-35.mp4

35.6M

04_W8_L22_P4-Recognition_results_14-14.mp4

33.9M

01_W9_L23_P1-Data_fitting_and_norms_11-36.mp4

25.4M

02_W9_L23_P2-Comparison_of_L2_and_L1_norms_11-13.mp4

29.8M

03_W9_L23_P3-Underdetermined_systems_11-57.mp4

40.0M

04_W9_L23_P4-Overdetermined_systems_13-14.mp4

25.6M

01_W9_L24_P1-Signal_Reconstruction_9-28.mp4

40.2M

02_W9_L24_P2-Linear_algebra_and_underdetermined_systems_12-19.mp4

37.8M

03_W9_L24_P3-Circumventing_Nyquist_16-12.mp4

39.9M

04_W9_L24_P4-Implementing_a_compressive_sensing_signal_reconstruction_12-52.mp4

32.8M

01_W9_L25_P1-Image_analysis_and_reconstruction_12-52.mp4

30.3M

02_W9_L25_P2-Image_Compression_11-30.mp4

33.7M

03_W9_L25_P3-Sampling_and_construction_of_Axb_12-11.mp4

41.5M

04_W9_L25_P4-Sampling_masks_and_image_reconstruction_14-28.mp4

33.3M

01_W10_L26_P1-Basic_techniques_for_solving_PDEs_9-53.mp4

31.6M

02_W10_L26_P2-Basis_expansion_techniques_8-34.mp4

35.0M

03_W10_L26_P3-The_nonlinear_schrodinger_equation_14-39.mp4

50.8M

04_W10_L26_P4-The_2-soliton_breather_solution_17-58.mp4

35.8M

01_W10_L27_P1-Computing_the_best_low-rank_basis_11-46.mp4

26.5M

02_W10_L27_P2-Applying_orthogonality_9-43.mp4

31.4M

03_W10_L27_P3-Comparison_of_low-rank_approximations_11-05.mp4

26.8M

04_W10_L27_P4-Dynamics_of_two-mode_approximation_8-33.mp4

42.3M

01_W10_L28_P1-Applying_the_reduction_techniques_to_PDEs-__water_waves_14-38.mp4

32.8M

02_W10_L28_P2-The_water_waves_in_the_right_basis_10-49.mp4

29.4M

03_W10_L28_P3-reducing_the_mode-locked_laser_problem_9-32.mp4

30.4M

04_W10_L28_P4-reduction_of_a_neuro-sensory_systems_10-42.mp4

119 files

OGG VIDEO

BACK

12.7M

01_Course_Overview.ogv

40.7M

01_Course_Introduction_9-30.ogv

11.5M

01_Use_of_MATLAB_for_the__course_2-41.ogv

44.0M

01_W01_L01_P01_-_Basics_of_the_Fourier_Transform_10-16.ogv

43.0M

02_W01_L01_P02_-_Representation_of_signals_as_frequencies_10-01.ogv

57.5M

03_W01_L01_P03_-_Implementing_the_FFT_routine_13-24.ogv

41.1M

04_W01_L01_P04_-_Derivatives_with_the_FFT_9-35.ogv

35.2M

01_W01_L02_P01_-_The_FFT_for_Radar_8-13.ogv

48.8M

02_W01_L02_P02_-_Signals_FFT_and_noise_11-22.ogv

32.5M

03_W01_L02_P03_-_White_noise_on_signals_7-35.ogv

42.7M

04_W01_L02_P04_-_Denoising_via_filtering_9-56.ogv

30.0M

05_W01_L02_P05_-_Signal_detection_and_thresholding_7-00.ogv

45.3M

01_W01_L03_P01_-_Averaging_over_white-noise_in_signals_10-33.ogv

53.3M

02_W01_L03_P02_-_Convergence_to_signal_through_repeated_sampling_12-25.ogv

65.9M

03_W01_L03_P03_-_Moving_signals_and_averaging_in_frequency_15-23.ogv

43.2M

04_W01_L03_P04_-_Signal_detection_through_averaging_and_averaging_10-04.ogv

41.1M

01_W2_L4_P1-A_Window_for_Fourier_Transforming_9-35.ogv

43.1M

02_W2_L4_P2-The_Gabor_Transform_10-03.ogv

39.0M

03_W2_L4_P3-Propeties_of_the_Gabor_Transform_9-06.ogv

41.7M

04_W2_L4_P4-Trade-offs_in_time-frequency_representations_9-45.ogv

34.9M

05_W2_L4_P5-Other_short-time_transforms_8-10.ogv

54.2M

01_W2_L5_P1-Introduction_to_Wavelets_12-40.ogv

38.1M

02_W2_L5_P2-The_Haar_wavelet_8-54.ogv

38.4M

03_W2_L5_P3-Some_wavelet_theorems_and_properties_8-59.ogv

37.2M

04_W2_L5_P4-Mexican_Hat_wavelet_8-44.ogv

44.1M

05_W2_L5_P5-More_wavelet_properties_10-19.ogv

39.8M

01_W2_L6_P1-Wavelet_building_blocks-_Dialations_and_Translations_9-17.ogv

42.3M

02_W2_L6_P2-An_analogy-Fourier_Analysis_and_eigenfunction_expansions_9-54.ogv

43.2M

03_W2_L6_P3-The_wavelet_basis_10-06.ogv

38.1M

04_W2_L6_P4-Multi-resolution_analysis_8-53.ogv

44.6M

01_W3_L7_P1-Building_signals_in_MATLAB_10-37.ogv

66.7M

02_W3_L7_P2-The_Gabor_Transform_15-54.ogv

70.9M

03_W3_L7_P3-Spectrograms_16-54.ogv

84.1M

01_W3_L8_P1-Filter_Design_Toolbox_19-59.ogv

105.2M

02_W3_L8_P2-Wavelet_Toolbox_25-05.ogv

53.3M

01_W4_L9_P1-Applications_of_image_processing_12-41.ogv

29.8M

02_W4_L9_P2-MATLAB_and_image_manipulation_7-02.ogv

57.6M

03_W4_L9_P3-Spectrum_of_Images_13-44.ogv

43.5M

01_W4_L10_P1-Image_Properties_10-08.ogv

43.9M

02_W4_L10_P2-Adding_Image_Noise_10-16.ogv

49.0M

03_W4_L10_P3-Basic_Image_Filter_Setup_11-24.ogv

29.1M

04_W4_L10_P4-Gaussian_Data_Filtering_6-48.ogv

48.9M

05_W4_L10_P5-Filter_Design_and_Image_Clean-up_11-26.ogv

43.6M

01_W4_L11_P1-_Filtering_through_diffusion_10-11.ogv

40.1M

02_W4_L11_P2_-_The_1D_Diffusion_Equation_9-22.ogv

43.4M

03_W4_L11_P3_-_Equivalence_of_Diffusion_with_Gaussian_Filtering_10-09.ogv

85.9M

04_W4_L11_P4_-_MATLAB_implementation_of_diffusion_filtering_20-05.ogv

45.9M

01_W5_L12_P1_-_Matrix_manipulations_on_data_10-44.ogv

37.6M

02_W5_L12_P2_-_Basics_of_the_SVD_8-47.ogv

42.3M

03_W5_L12_P3_-_Matrix_Decomposition_9-54.ogv

30.2M

04_W5_L12_P4_-_Properties_of_the_SVD_7-04.ogv

43.2M

05_W5_L12_P5_-_Computing_the_SVD_10-05.ogv

42.5M

01_W5_L13_P1_-_Review_of_SVD_9-55.ogv

50.6M

02_W5_L13_P2_-_Diagonalization_of_Matrices_11-50.ogv

40.3M

03_W5_L13_P3_-_SVD_Diagonalization_9-24.ogv

40.0M

04_W5_L13_P4_-_Theorems_of_the_SVD_9-21.ogv

39.9M

05_W5_L13_P5_-_Low-rank_Reductions_9-19.ogv

69.3M

01_W5_L14_P1_-_A_Spring_Mass_System_16-11.ogv

51.2M

02_W5_L14_P2_-_The_Variance_and_Covariance_of_the_Data_11-56.ogv

41.1M

03_W5_L14_P3_-_Covariance_Matrix_and_Redundancy_9-35.ogv

43.6M

04_W5_L14_P4_-_The_SVD_and_PCA_10-11.ogv

40.7M

01_W6_L15_P1-_Interpreting_the_covariance_matrix-diagonal_elements_9-30.ogv

41.3M

02_W6_L15_P2-Interpreting_the_covariance_matrix-off-diagonals_9-38.ogv

34.5M

03_W6_L15_P3-Relationship_to_eigenvectors-eigenvalues_8-03.ogv

42.4M

04_W6_L15_P4-SVD_versus_EIGS_9-53.ogv

47.9M

05_W6_L15_P5-Interpretation_for_spring-mass_system_11-11.ogv

51.1M

01_W6_L16_P1-Modal_expansions_11-55.ogv

45.9M

02_W6_L16_P2-SVD_for_basis_expansions_10-41.ogv

65.0M

03_W6_L16_P3-Low_rank_reconstructions_of_a_function_15-09.ogv

56.8M

04_W6_L16_P4-Another_low-rank_approximation_13-15.ogv

52.2M

01_W7_L17_P1_-_Independent_Components_-_The_Cocktail_Party_Problem_12-11.ogv

37.8M

02_W7_L17_P2_-_Signal_Separation_8-49.ogv

40.1M

03_W7_L17_P3_-_Separating_Images_9-22.ogv

61.9M

04_W7_L17_P4_-_Mathematical_Framework_and_the_SVD_14-13.ogv

43.6M

01_W7_L18_P1_-_Review_of_Mathematical_Algorithm_10-12.ogv

54.0M

02_W7_L18_P2_-_Computing_the_Principal_Directions_12-38.ogv

37.4M

03_W7_L18_P3_-_Computing_the_Stretching_10-06.ogv

43.2M

04_W7_L18_P4_-_Using_Kurtosis_for_Final_Analysis_10-06.ogv

38.5M

05_W7_L18_P5_-_Combining_all_the_Components_for_ICA_9-01.ogv

54.8M

01_W7_L19_P1_-_Algorithm_Overview_of_ICA_and_Image_Separation_12-47.ogv

40.7M

02_W7_L19_P2_-_Mixing_Images_9-29.ogv

62.2M

03_W7_L19_P3_-_Computing_the_Stretching_and_Rotation_14-30.ogv

65.6M

04_W7_L19_P4_-_Separating_the_Images_15-18.ogv

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01_W8_L20_P1-Introduction_to_recognition_ideas_14-27.ogv

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02_W8_L20_P2-Quantifying_image_recognition_13-16.ogv

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03_W8_L20_P3-Pre-processing_dog_cat_images_9-30.ogv

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04_W8_L20_P4-wavelet_transforming_dogs_cats_12-05.ogv

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01_W8_L21_P1-Wavelet_dogs_and_cats_10-18.ogv

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02_W8_L21_P2-Building_dog_cat_PCA_components_14-40.ogv

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03_W8_L21_P3-Features_10-54.ogv

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04_W8_L21_P4-linear_discrimination_9-42.ogv

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01_W8_L22_P1-Putting_all_the_algorithm_parts_together_11-12.ogv

43.2M

02_W8_L22_P2-Training_sets_10-07.ogv

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03_W8_L22_P3-The_linear_discriminant_14-35.ogv

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04_W8_L22_P4-Recognition_results_14-14.ogv

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01_W9_L23_P1-Data_fitting_and_norms_11-36.ogv

48.1M

02_W9_L23_P2-Comparison_of_L2_and_L1_norms_11-13.ogv

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03_W9_L23_P3-Underdetermined_systems_11-57.ogv

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04_W9_L23_P4-Overdetermined_systems_13-14.ogv

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01_W9_L24_P1-Signal_Reconstruction_9-28.ogv

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02_W9_L24_P2-Linear_algebra_and_underdetermined_systems_12-19.ogv

69.4M

03_W9_L24_P3-Circumventing_Nyquist_16-12.ogv

55.0M

04_W9_L24_P4-Implementing_a_compressive_sensing_signal_reconstruction_12-52.ogv

55.1M

01_W9_L25_P1-Image_analysis_and_reconstruction_12-52.ogv

49.3M

02_W9_L25_P2-Image_Compression_11-30.ogv

52.1M

03_W9_L25_P3-Sampling_and_construction_of_Axb_12-11.ogv

61.9M

04_W9_L25_P4-Sampling_masks_and_image_reconstruction_14-28.ogv

42.3M

01_W10_L26_P1-Basic_techniques_for_solving_PDEs_9-53.ogv

36.8M

02_W10_L26_P2-Basis_expansion_techniques_8-34.ogv

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03_W10_L26_P3-The_nonlinear_schrodinger_equation_14-39.ogv

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04_W10_L26_P4-The_2-soliton_breather_solution_17-58.ogv

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01_W10_L27_P1-Computing_the_best_low-rank_basis_11-46.ogv

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02_W10_L27_P2-Applying_orthogonality_9-43.ogv

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03_W10_L27_P3-Comparison_of_low-rank_approximations_11-05.ogv

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04_W10_L27_P4-Dynamics_of_two-mode_approximation_8-33.ogv

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01_W10_L28_P1-Applying_the_reduction_techniques_to_PDEs-__water_waves_14-38.ogv

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02_W10_L28_P2-The_water_waves_in_the_right_basis_10-49.ogv

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03_W10_L28_P3-reducing_the_mode-locked_laser_problem_9-32.ogv

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04_W10_L28_P4-reduction_of_a_neuro-sensory_systems_10-42.ogv

1 file

PDF

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SINGLE PAGE PROCESSED JP2 ZIP

119 files

SUBRIP

BACK

4.0K

01_Course_Overview.srt

12.6K

01_Course_Introduction_9-30.srt

3.2K

01_Use_of_MATLAB_for_the__course_2-41.srt

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01_W01_L01_P01_-_Basics_of_the_Fourier_Transform_10-16.srt

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02_W01_L01_P02_-_Representation_of_signals_as_frequencies_10-01.srt

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03_W01_L01_P03_-_Implementing_the_FFT_routine_13-24.srt

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04_W01_L01_P04_-_Derivatives_with_the_FFT_9-35.srt

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01_W01_L02_P01_-_The_FFT_for_Radar_8-13.srt

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02_W01_L02_P02_-_Signals_FFT_and_noise_11-22.srt

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03_W01_L02_P03_-_White_noise_on_signals_7-35.srt

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04_W01_L02_P04_-_Denoising_via_filtering_9-56.srt

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05_W01_L02_P05_-_Signal_detection_and_thresholding_7-00.srt

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01_W01_L03_P01_-_Averaging_over_white-noise_in_signals_10-33.srt

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02_W01_L03_P02_-_Convergence_to_signal_through_repeated_sampling_12-25.srt

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03_W01_L03_P03_-_Moving_signals_and_averaging_in_frequency_15-23.srt

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04_W01_L03_P04_-_Signal_detection_through_averaging_and_averaging_10-04.srt

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01_W2_L4_P1-A_Window_for_Fourier_Transforming_9-35.srt

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02_W2_L4_P2-The_Gabor_Transform_10-03.srt

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03_W2_L4_P3-Propeties_of_the_Gabor_Transform_9-06.srt

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04_W2_L4_P4-Trade-offs_in_time-frequency_representations_9-45.srt

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05_W2_L4_P5-Other_short-time_transforms_8-10.srt

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01_W2_L5_P1-Introduction_to_Wavelets_12-40.srt

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02_W2_L5_P2-The_Haar_wavelet_8-54.srt

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03_W2_L5_P3-Some_wavelet_theorems_and_properties_8-59.srt

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04_W2_L5_P4-Mexican_Hat_wavelet_8-44.srt

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05_W2_L5_P5-More_wavelet_properties_10-19.srt

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01_W2_L6_P1-Wavelet_building_blocks-_Dialations_and_Translations_9-17.srt

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02_W2_L6_P2-An_analogy-Fourier_Analysis_and_eigenfunction_expansions_9-54.srt

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04_W2_L6_P4-Multi-resolution_analysis_8-53.srt

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01_W3_L7_P1-Building_signals_in_MATLAB_10-37.srt

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02_W3_L7_P2-The_Gabor_Transform_15-54.srt

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03_W3_L7_P3-Spectrograms_16-54.srt

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02_W3_L8_P2-Wavelet_Toolbox_25-05.srt

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01_W4_L9_P1-Applications_of_image_processing_12-41.srt

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02_W4_L9_P2-MATLAB_and_image_manipulation_7-02.srt

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03_W4_L9_P3-Spectrum_of_Images_13-44.srt

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01_W4_L10_P1-Image_Properties_10-08.srt

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03_W4_L10_P3-Basic_Image_Filter_Setup_11-24.srt

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04_W4_L10_P4-Gaussian_Data_Filtering_6-48.srt

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05_W4_L10_P5-Filter_Design_and_Image_Clean-up_11-26.srt

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01_W4_L11_P1-_Filtering_through_diffusion_10-11.srt

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02_W4_L11_P2_-_The_1D_Diffusion_Equation_9-22.srt

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03_W4_L11_P3_-_Equivalence_of_Diffusion_with_Gaussian_Filtering_10-09.srt

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04_W4_L11_P4_-_MATLAB_implementation_of_diffusion_filtering_20-05.srt

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01_W5_L12_P1_-_Matrix_manipulations_on_data_10-44.srt

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02_W5_L12_P2_-_Basics_of_the_SVD_8-47.srt

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03_W5_L12_P3_-_Matrix_Decomposition_9-54.srt

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04_W5_L12_P4_-_Properties_of_the_SVD_7-04.srt

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05_W5_L12_P5_-_Computing_the_SVD_10-05.srt

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01_W5_L13_P1_-_Review_of_SVD_9-55.srt

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02_W5_L13_P2_-_Diagonalization_of_Matrices_11-50.srt

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03_W5_L13_P3_-_SVD_Diagonalization_9-24.srt

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04_W5_L13_P4_-_Theorems_of_the_SVD_9-21.srt

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05_W5_L13_P5_-_Low-rank_Reductions_9-19.srt

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01_W5_L14_P1_-_A_Spring_Mass_System_16-11.srt

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02_W5_L14_P2_-_The_Variance_and_Covariance_of_the_Data_11-56.srt

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03_W5_L14_P3_-_Covariance_Matrix_and_Redundancy_9-35.srt

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04_W5_L14_P4_-_The_SVD_and_PCA_10-11.srt

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01_W6_L15_P1-_Interpreting_the_covariance_matrix-diagonal_elements_9-30.srt

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02_W6_L15_P2-Interpreting_the_covariance_matrix-off-diagonals_9-38.srt

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03_W6_L15_P3-Relationship_to_eigenvectors-eigenvalues_8-03.srt

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04_W6_L15_P4-SVD_versus_EIGS_9-53.srt

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05_W6_L15_P5-Interpretation_for_spring-mass_system_11-11.srt

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01_W6_L16_P1-Modal_expansions_11-55.srt

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02_W6_L16_P2-SVD_for_basis_expansions_10-41.srt

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03_W6_L16_P3-Low_rank_reconstructions_of_a_function_15-09.srt

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04_W6_L16_P4-Another_low-rank_approximation_13-15.srt

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01_W7_L17_P1_-_Independent_Components_-_The_Cocktail_Party_Problem_12-11.srt

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02_W7_L17_P2_-_Signal_Separation_8-49.srt

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03_W7_L17_P3_-_Separating_Images_9-22.srt

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04_W7_L17_P4_-_Mathematical_Framework_and_the_SVD_14-13.srt

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01_W7_L18_P1_-_Review_of_Mathematical_Algorithm_10-12.srt

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02_W7_L18_P2_-_Computing_the_Principal_Directions_12-38.srt

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03_W7_L18_P3_-_Computing_the_Stretching_10-06.srt

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04_W7_L18_P4_-_Using_Kurtosis_for_Final_Analysis_10-06.srt

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05_W7_L18_P5_-_Combining_all_the_Components_for_ICA_9-01.srt

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01_W7_L19_P1_-_Algorithm_Overview_of_ICA_and_Image_Separation_12-47.srt

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02_W7_L19_P2_-_Mixing_Images_9-29.srt

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03_W7_L19_P3_-_Computing_the_Stretching_and_Rotation_14-30.srt

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04_W7_L19_P4_-_Separating_the_Images_15-18.srt

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01_W8_L20_P1-Introduction_to_recognition_ideas_14-27.srt

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02_W8_L20_P2-Quantifying_image_recognition_13-16.srt

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03_W8_L20_P3-Pre-processing_dog_cat_images_9-30.srt

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04_W8_L20_P4-wavelet_transforming_dogs_cats_12-05.srt

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01_W8_L21_P1-Wavelet_dogs_and_cats_10-18.srt

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02_W8_L21_P2-Building_dog_cat_PCA_components_14-40.srt

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03_W8_L21_P3-Features_10-54.srt

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04_W8_L21_P4-linear_discrimination_9-42.srt

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01_W8_L22_P1-Putting_all_the_algorithm_parts_together_11-12.srt

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02_W8_L22_P2-Training_sets_10-07.srt

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03_W8_L22_P3-The_linear_discriminant_14-35.srt

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04_W8_L22_P4-Recognition_results_14-14.srt

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01_W9_L23_P1-Data_fitting_and_norms_11-36.srt

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02_W9_L23_P2-Comparison_of_L2_and_L1_norms_11-13.srt

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03_W9_L23_P3-Underdetermined_systems_11-57.srt

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04_W9_L23_P4-Overdetermined_systems_13-14.srt

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01_W9_L24_P1-Signal_Reconstruction_9-28.srt

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02_W9_L24_P2-Linear_algebra_and_underdetermined_systems_12-19.srt

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03_W9_L24_P3-Circumventing_Nyquist_16-12.srt

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04_W9_L24_P4-Implementing_a_compressive_sensing_signal_reconstruction_12-52.srt

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01_W9_L25_P1-Image_analysis_and_reconstruction_12-52.srt

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02_W9_L25_P2-Image_Compression_11-30.srt

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03_W9_L25_P3-Sampling_and_construction_of_Axb_12-11.srt

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04_W9_L25_P4-Sampling_masks_and_image_reconstruction_14-28.srt

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01_W10_L26_P1-Basic_techniques_for_solving_PDEs_9-53.srt

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02_W10_L26_P2-Basis_expansion_techniques_8-34.srt

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03_W10_L26_P3-The_nonlinear_schrodinger_equation_14-39.srt

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04_W10_L26_P4-The_2-soliton_breather_solution_17-58.srt

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01_W10_L27_P1-Computing_the_best_low-rank_basis_11-46.srt

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02_W10_L27_P2-Applying_orthogonality_9-43.srt

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03_W10_L27_P3-Comparison_of_low-rank_approximations_11-05.srt

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04_W10_L27_P4-Dynamics_of_two-mode_approximation_8-33.srt

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01_W10_L28_P1-Applying_the_reduction_techniques_to_PDEs-__water_waves_14-38.srt

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02_W10_L28_P2-The_water_waves_in_the_right_basis_10-49.srt

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03_W10_L28_P3-reducing_the_mode-locked_laser_problem_9-32.srt

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04_W10_L28_P4-reduction_of_a_neuro-sensory_systems_10-42.srt

154 files

TEXT

BACK

2.7K

01_Course_Overview.txt

8.7K

01_Course_Introduction_9-30.txt

2.2K

01_Use_of_MATLAB_for_the__course_2-41.txt

7.9K

01_W01_L01_P01_-_Basics_of_the_Fourier_Transform_10-16.txt

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02_W01_L01_P02_-_Representation_of_signals_as_frequencies_10-01.txt

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03_W01_L01_P03_-_Implementing_the_FFT_routine_13-24.txt

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04_W01_L01_P04_-_Derivatives_with_the_FFT_9-35.txt

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01_W01_L02_P01_-_The_FFT_for_Radar_8-13.txt

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02_W01_L02_P02_-_Signals_FFT_and_noise_11-22.txt

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03_W01_L02_P03_-_White_noise_on_signals_7-35.txt

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04_W01_L02_P04_-_Denoising_via_filtering_9-56.txt

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05_W01_L02_P05_-_Signal_detection_and_thresholding_7-00.txt

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01_W01_L03_P01_-_Averaging_over_white-noise_in_signals_10-33.txt

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02_W01_L03_P02_-_Convergence_to_signal_through_repeated_sampling_12-25.txt

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03_W01_L03_P03_-_Moving_signals_and_averaging_in_frequency_15-23.txt

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04_W01_L03_P04_-_Signal_detection_through_averaging_and_averaging_10-04.txt

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01_W2_L4_P1-A_Window_for_Fourier_Transforming_9-35.txt

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02_W2_L4_P2-The_Gabor_Transform_10-03.txt

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03_W2_L4_P3-Propeties_of_the_Gabor_Transform_9-06.txt

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04_W2_L4_P4-Trade-offs_in_time-frequency_representations_9-45.txt

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05_W2_L4_P5-Other_short-time_transforms_8-10.txt

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01_W2_L5_P1-Introduction_to_Wavelets_12-40.txt

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02_W2_L5_P2-The_Haar_wavelet_8-54.txt

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03_W2_L5_P3-Some_wavelet_theorems_and_properties_8-59.txt

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04_W2_L5_P4-Mexican_Hat_wavelet_8-44.txt

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05_W2_L5_P5-More_wavelet_properties_10-19.txt

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01_W2_L6_P1-Wavelet_building_blocks-_Dialations_and_Translations_9-17.txt

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02_W2_L6_P2-An_analogy-Fourier_Analysis_and_eigenfunction_expansions_9-54.txt

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03_W2_L6_P3-The_wavelet_basis_10-06.txt

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04_W2_L6_P4-Multi-resolution_analysis_8-53.txt

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01_W3_L7_P1-Building_signals_in_MATLAB_10-37.txt

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02_W3_L7_P2-The_Gabor_Transform_15-54.txt

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03_W3_L7_P3-Spectrograms_16-54.txt

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01_W3_L8_P1-Filter_Design_Toolbox_19-59.txt

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02_W3_L8_P2-Wavelet_Toolbox_25-05.txt

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01_W4_L9_P1-Applications_of_image_processing_12-41.txt

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02_W4_L9_P2-MATLAB_and_image_manipulation_7-02.txt

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03_W4_L9_P3-Spectrum_of_Images_13-44.txt

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01_W4_L10_P1-Image_Properties_10-08.txt

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02_W4_L10_P2-Adding_Image_Noise_10-16.txt

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03_W4_L10_P3-Basic_Image_Filter_Setup_11-24.txt

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04_W4_L10_P4-Gaussian_Data_Filtering_6-48.txt

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05_W4_L10_P5-Filter_Design_and_Image_Clean-up_11-26.txt

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01_W4_L11_P1-_Filtering_through_diffusion_10-11.txt

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02_W4_L11_P2_-_The_1D_Diffusion_Equation_9-22.txt

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03_W4_L11_P3_-_Equivalence_of_Diffusion_with_Gaussian_Filtering_10-09.txt

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04_W4_L11_P4_-_MATLAB_implementation_of_diffusion_filtering_20-05.txt

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01_W5_L12_P1_-_Matrix_manipulations_on_data_10-44.txt

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02_W5_L12_P2_-_Basics_of_the_SVD_8-47.txt

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03_W5_L12_P3_-_Matrix_Decomposition_9-54.txt

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04_W5_L12_P4_-_Properties_of_the_SVD_7-04.txt

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05_W5_L12_P5_-_Computing_the_SVD_10-05.txt

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01_W5_L13_P1_-_Review_of_SVD_9-55.txt

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02_W5_L13_P2_-_Diagonalization_of_Matrices_11-50.txt

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04_W5_L13_P4_-_Theorems_of_the_SVD_9-21.txt

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05_W5_L13_P5_-_Low-rank_Reductions_9-19.txt

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02_W5_L14_P2_-_The_Variance_and_Covariance_of_the_Data_11-56.txt

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03_W5_L14_P3_-_Covariance_Matrix_and_Redundancy_9-35.txt

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04_W5_L14_P4_-_The_SVD_and_PCA_10-11.txt

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01_W6_L15_P1-_Interpreting_the_covariance_matrix-diagonal_elements_9-30.txt

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02_W6_L15_P2-Interpreting_the_covariance_matrix-off-diagonals_9-38.txt

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03_W6_L15_P3-Relationship_to_eigenvectors-eigenvalues_8-03.txt

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04_W6_L15_P4-SVD_versus_EIGS_9-53.txt

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05_W6_L15_P5-Interpretation_for_spring-mass_system_11-11.txt

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01_W6_L16_P1-Modal_expansions_11-55.txt

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02_W6_L16_P2-SVD_for_basis_expansions_10-41.txt

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03_W6_L16_P3-Low_rank_reconstructions_of_a_function_15-09.txt

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04_W6_L16_P4-Another_low-rank_approximation_13-15.txt

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01_W7_L17_P1_-_Independent_Components_-_The_Cocktail_Party_Problem_12-11.txt

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02_W7_L17_P2_-_Signal_Separation_8-49.txt

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03_W7_L17_P3_-_Separating_Images_9-22.txt

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04_W7_L17_P4_-_Mathematical_Framework_and_the_SVD_14-13.txt

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01_W7_L18_P1_-_Review_of_Mathematical_Algorithm_10-12.txt

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02_W7_L18_P2_-_Computing_the_Principal_Directions_12-38.txt

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03_W7_L18_P3_-_Computing_the_Stretching_10-06.txt

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04_W7_L18_P4_-_Using_Kurtosis_for_Final_Analysis_10-06.txt

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05_W7_L18_P5_-_Combining_all_the_Components_for_ICA_9-01.txt

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01_W7_L19_P1_-_Algorithm_Overview_of_ICA_and_Image_Separation_12-47.txt

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02_W7_L19_P2_-_Mixing_Images_9-29.txt

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03_W7_L19_P3_-_Computing_the_Stretching_and_Rotation_14-30.txt

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04_W7_L19_P4_-_Separating_the_Images_15-18.txt

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01_W8_L20_P1-Introduction_to_recognition_ideas_14-27.txt

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02_W8_L20_P2-Quantifying_image_recognition_13-16.txt

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03_W8_L20_P3-Pre-processing_dog_cat_images_9-30.txt

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04_W8_L20_P4-wavelet_transforming_dogs_cats_12-05.txt

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01_W8_L21_P1-Wavelet_dogs_and_cats_10-18.txt

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02_W8_L21_P2-Building_dog_cat_PCA_components_14-40.txt

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03_W8_L21_P3-Features_10-54.txt

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04_W8_L21_P4-linear_discrimination_9-42.txt

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01_W8_L22_P1-Putting_all_the_algorithm_parts_together_11-12.txt

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02_W8_L22_P2-Training_sets_10-07.txt

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03_W8_L22_P3-The_linear_discriminant_14-35.txt

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04_W8_L22_P4-Recognition_results_14-14.txt

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01_W9_L23_P1-Data_fitting_and_norms_11-36.txt

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02_W9_L23_P2-Comparison_of_L2_and_L1_norms_11-13.txt

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03_W9_L23_P3-Underdetermined_systems_11-57.txt

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04_W9_L23_P4-Overdetermined_systems_13-14.txt

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01_W9_L24_P1-Signal_Reconstruction_9-28.txt

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02_W9_L24_P2-Linear_algebra_and_underdetermined_systems_12-19.txt

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03_W9_L24_P3-Circumventing_Nyquist_16-12.txt

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04_W9_L24_P4-Implementing_a_compressive_sensing_signal_reconstruction_12-52.txt

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01_W9_L25_P1-Image_analysis_and_reconstruction_12-52.txt

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02_W9_L25_P2-Image_Compression_11-30.txt

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03_W9_L25_P3-Sampling_and_construction_of_Axb_12-11.txt

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04_W9_L25_P4-Sampling_masks_and_image_reconstruction_14-28.txt

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01_W10_L26_P1-Basic_techniques_for_solving_PDEs_9-53.txt

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02_W10_L26_P2-Basis_expansion_techniques_8-34.txt

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03_W10_L26_P3-The_nonlinear_schrodinger_equation_14-39.txt

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04_W10_L26_P4-The_2-soliton_breather_solution_17-58.txt

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01_W10_L27_P1-Computing_the_best_low-rank_basis_11-46.txt

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02_W10_L27_P2-Applying_orthogonality_9-43.txt

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03_W10_L27_P3-Comparison_of_low-rank_approximations_11-05.txt

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04_W10_L27_P4-Dynamics_of_two-mode_approximation_8-33.txt

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01_W10_L28_P1-Applying_the_reduction_techniques_to_PDEs-__water_waves_14-38.txt

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02_W10_L28_P2-The_water_waves_in_the_right_basis_10-49.txt

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03_W10_L28_P3-reducing_the_mode-locked_laser_problem_9-32.txt

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04_W10_L28_P4-reduction_of_a_neuro-sensory_systems_10-42.txt

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[Coursera] Computational Methods for Data Analysis (University of Washington) (compmethods)

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