[et_pb_section fb_built=”1″ fullwidth=”on” _builder_version=”4.27.0″ background_image=”https:\/\/ece.iisc.ac.in\/~cmurthy\/wp-content\/uploads\/2024\/09\/GOPR0015-scaled.jpg” global_colors_info=”{}”][et_pb_fullwidth_header title=”E2 212: Matrix Theory” content_max_width=”none” module_class=”sub_header” _builder_version=”4.27.0″ title_font=”|on|||” title_text_color=”#FFFFFF” title_font_size=”50px” background_color=”rgba(255, 255, 255, 0)” background_image=”https:\/\/ece.iisc.ac.in\/~cmurthy\/wp-content\/uploads\/2024\/09\/abstract-1438441.jpg” parallax=”on” button_one_letter_spacing_hover=”0″ button_two_letter_spacing_hover=”0″ global_colors_info=”{}” button_one_text_size__hover_enabled=”off” button_two_text_size__hover_enabled=”off” button_one_text_color__hover_enabled=”off” button_two_text_color__hover_enabled=”off” button_one_border_width__hover_enabled=”off” button_two_border_width__hover_enabled=”off” button_one_border_color__hover_enabled=”off” button_two_border_color__hover_enabled=”off” button_one_border_radius__hover_enabled=”off” button_two_border_radius__hover_enabled=”off” button_one_letter_spacing__hover_enabled=”on” button_one_letter_spacing__hover=”0″ button_two_letter_spacing__hover_enabled=”on” button_two_letter_spacing__hover=”0″ button_one_bg_color__hover_enabled=”off” button_two_bg_color__hover_enabled=”off”][\/et_pb_fullwidth_header][\/et_pb_section][et_pb_section fb_built=”1″ _builder_version=”4.27.0″ _module_preset=”default” global_colors_info=”{}”][et_pb_row _builder_version=”4.27.0″ _module_preset=”default” custom_padding=”|||0px||” global_colors_info=”{}”][et_pb_column type=”4_4″ _builder_version=”4.27.0″ _module_preset=”default” global_colors_info=”{}”][et_pb_text _builder_version=”4.27.0″ _module_preset=”default” text_orientation=”justified” custom_padding=”|||11px||” hover_enabled=”0″ global_colors_info=”{}” sticky_enabled=”0″]<\/p>\n
Instructor:<\/strong>\u00a0Chandra R. Murthy (cmurthy at iisc dot ac dot in) Textbooks:<\/strong> Homeworks\/Assignments: 25%. Homeworks are posted\u00a0here<\/a>.<\/p>\n<\/div>\n
Class hours:<\/strong>\u00a0MWF 12-1pm, Online.
TAs<\/strong>: Chirag Ramesh and Nagabhushan S. N.
TA Hours<\/strong>: Tuesdays and Wednesdays 5-6pm
Problem Session<\/strong>: Saturdays 9-10am<\/p>\n
1. Horn and Johnson, Matrix Analysis, Cambridge University Press
2. David Lewis, Matrix Theory, Allied Publishers
3. Golub and Van Loan, Matrix Computations, 3rd Ed., John Hopkins University Press
4. Gilbert Strang, Linear Algebra and its Application, 3rd Ed., Harcourth Brace Jovanovich Pubs.\u00a0Also see the video lectures<\/strong>\u00a0here<\/a>.<\/p>\n<\/div>\n\u00a0<\/h3>\n
Syllabus:<\/h3>\n
\n\n
\n S. No.<\/th>\n Topic<\/th>\n Num. Lectures<\/th>\n<\/tr>\n \n 1<\/td>\n Background and review<\/td>\n 3<\/td>\n<\/tr>\n \n 2<\/td>\n Eigenvalues and eigenvectors<\/td>\n 5<\/td>\n<\/tr>\n \n 3<\/td>\n Singular value decomposition<\/td>\n 3<\/td>\n<\/tr>\n \n 4<\/td>\n The quadratic form, error analysis<\/td>\n 4<\/td>\n<\/tr>\n \n 5<\/td>\n Gaussian elimination and LU factorization<\/td>\n 5<\/td>\n<\/tr>\n \n 6<\/td>\n The full-rank least-squares problem<\/td>\n 3<\/td>\n<\/tr>\n \n 7<\/td>\n Rank deficient LS, generalized pseudoinverses, PCA, QR factorization<\/td>\n 6<\/td>\n<\/tr>\n \n 8<\/td>\n Toeplitz and related systems<\/td>\n 2<\/td>\n<\/tr>\n \n \u00a0<\/td>\n Total<\/strong><\/td>\n 31<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/div>\n<\/div>\n \u00a0<\/h2>\n
Grading [Tentative]<\/h2>\n
Midterm 1: TBD, in class: 25%.
Midterm 2: TBD, in class: 25%.
Final: TBD: 25%.
Note:\u00a0there will be no makeup exams.<\/strong><\/p>\n<\/div>\n\u00a0<\/h2>\n
Homeworks<\/h2>\n
\u00a0<\/h2>\n
Lectures<\/h2>\n