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University of California, Berkeley course. James Demmel is the instructor; this role does not establish authorship of each note. Spring 1996 is the course term.

Course homepage: people.eecs.berkeley.edu/~demmel/cs267/

By James Demmel.

Online text: people.eecs.berkeley.edu/~demmel/cs267/lecture25/lecture25a.html

Cited passages: James Demmel, CS267 supplemental notes, 12 March 1996, How Multigrid Damps High Frequencies: sine eigenvectors and the one-third high-frequency bound.

Additional cited passages: diagonal-2 tridiagonal Poisson matrix, error eigenvector expansion, weighted-iteration multiplier, and concluding attenuation statement. The heading dates the lecture to 12 March 1996.

University of California, Berkeley course, Fall 2009. Course instructor: James Demmel, verified by his faculty homepage. This association does not establish authorship of every course resource.

Instructor and course listing: people.eecs.berkeley.edu/~demmel/

Lecture notes in Math 221, Matrix Computations, Fall 2009, dated 10 November 2009 in the heading. The page has no explicit author byline. James Demmel is the verified course instructor; the University of California, Berkeley EECS faculty website hosts the notes. No separate publication date or institutional authorship is asserted.

Online text: people.eecs.berkeley.edu/~demmel/ma221_Fall09/Lectures/Lecture_21.html

Cited passages: Basic iterative methods, splitting and recurrence (*); spectral-radius lemmas and convergence-for-all-starts theorem; Jacobi and Gauss-Seidel component loops; strict row diagonal dominance, Theorem 1 and proof; 1D Dirichlet Poisson matrix and sine eigenvectors.

Additional cited passages: opening solver building blocks; Gauss-Seidel component loop, splitting, ordering remark and red-black scheduling; Theorem 1, strict row diagonal dominance; Theorem 3, SOR convergence for symmetric positive-definite matrices with the ω = 1 specialization. The lecture date and instructor association above remain distinct from author bylines and publication dates.

University of California, Berkeley course, Fall 2023. The course homepage identifies James Demmel as instructor and labels the course Matrix Computations / Numerical Linear Algebra. The instructor role does not establish authorship of each resource.

Course homepage: people.eecs.berkeley.edu/~demmel/ma221_Fall23/

Lecture notes in Math 221, Matrix Computations, Fall 2023, dated 1 December 2023 in the heading. No explicit author byline or institutional authorship is established. The University of California, Berkeley EECS faculty website hosts the notes; James Demmel is the course instructor. The lecture date is distinct from any publication or revision date.

Lecture notes: people.eecs.berkeley.edu/~demmel/ma221_Fall23/Lectures/Lecture_15.pdf

Cited passages: PDF p. 1 heading and opening left/symmetric transformations; PDF p. 1, Preconditioned CG algorithm and equivalent symmetric system; PDF p. 1, goals (1) and (2), M = I and M = A comparison, example (1) Jacobi preconditioning; PDF p. 2, example (3) triangular factor solves; Course homepage, title and Instructor section, web lines 2–14.