What Happens to Av^j When j Exceeds Rank r in SVD?

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Discussion Overview

The discussion revolves around the behavior of the product Av^j in the context of Singular Value Decomposition (SVD) when the index j exceeds the rank r of the matrix A. Participants are exploring the implications of this scenario, particularly for values of j greater than r.

Discussion Character

  • Exploratory, Technical explanation, Debate/contested

Main Points Raised

  • One participant states that for 1 <= j <= r, Av^j equals sigma^j * u^j.
  • The same participant questions what Av^j becomes for r + 1 <= j <= n, indicating a gap in understanding for this range.
  • Other participants express uncertainty about the topic, with some indicating they do not have a clear idea or solution.

Areas of Agreement / Disagreement

There is no consensus among participants, as several express uncertainty and lack of knowledge regarding the behavior of Av^j for j greater than r.

Contextual Notes

The discussion lacks detailed exploration of the mathematical properties or definitions that might clarify the behavior of Av^j for j > r, leaving assumptions and implications unresolved.

stuck_on_math
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Let A be an m × n matrix of rank r and let A = U\SigmaV be an SVD of A. Prove that

Av^{j}= sigma^j* u^{j} for 1<=j<=r

What is Av^j for r + 1<=j<=n?
 
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Well, what do you think?
 
I don't know, that's why I am asking
 
You must have some idea.
 
I really don't
 

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