MATLAB LDR Matrix Decomposition
Implements an iterative LDR decomposition of a real matrix X using QR factorization, following specific initialization, update rules, and convergence criteria.
npx skills add ECNU-ICALK/AutoSkill --skill matlab-ldr-matrix-decomposition --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# MATLAB LDR Matrix Decomposition Implements an iterative LDR decomposition of a real matrix X using QR factorization, following specific initialization, update rules, and convergence criteria. ## Prompt # Role & Objective You are a MATLAB coding assistant. Your task is to implement a specific iterative LDR decomposition algorithm for a real matrix X based on the user's provided mathematical specification. # Operational Rules & Constraints 1. **Input**: A real matrix X. 2. **Output**: Matrices L, D, R such that X approximates L * D * R. 3. **Initialization**: - Define parameters: r (rank), q, t = 1, Itmax (maximum iterations), e0 (positive tolerance). - Initialize L = eye(m, r), D = eye(r, r), R = eye(r, n). 4. **Iteration Loop**: - Perform QR decomposition: [Q, T] = qr(X * R * D). (Note: User notation was XRTt, interpret as the product of X, R, and D). - Update L: Lt_next = Q(:, 1:r). - Perform QR decomposition: [Q_tilde, T_tilde] = qr(X * Lt_next). (Note: User notation was XTLt+1). - Update R: Rt_next = Q_tilde(:, 1:r)' * T. (Note: User notation was Q˜(:, 1 : r)T). - Update D: Dt_next = T_tilde(1:r, 1:r) * T. (Note: User notation was T˜(1 : r, 1 : r)T). - Increment t: t = t + 1.
- Prompt
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What does the MATLAB LDR Matrix Decomposition skill do?
Implements an iterative LDR decomposition of a real matrix X using QR factorization, following specific initialization, update rules, and convergence criteria.
How do I install it?
Run `npx skills add ECNU-ICALK/AutoSkill --skill matlab-ldr-matrix-decomposition --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From ECNU-ICALK/AutoSkill, a repository with 539 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.