Matrix Problem: Solving for H(^T)*H with P and H matrices

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Discussion Overview

The discussion revolves around the mathematical problem of determining the expression for H(^T)*H, where H is defined in terms of a matrix P. The context includes exploring properties of matrices, specifically focusing on the implications of P being a unit vector and the nature of the resulting matrix H.

Discussion Character

  • Technical explanation
  • Mathematical reasoning
  • Debate/contested

Main Points Raised

  • Some participants clarify that P is an n x 1 matrix and that P(^T)*P = 1 implies P is a unit vector.
  • There is confusion regarding whether to treat the scalar 2 as a 1 x 1 matrix when calculating H.
  • One participant asserts that H is symmetric and that H(^T)H = I_n, suggesting it holds for any n x n matrix.
  • Another participant introduces the concept of H as a reflection operator and discusses the implications of reflecting twice.
  • There is a correction regarding the formulation of H, emphasizing that it should be H = I - 2PP(^T) rather than H = I - 2P(^T)P.
  • Participants discuss the dimensionality of matrices involved, noting that PP(^T) is an n x n matrix, while P(^T)P is a scalar when n = 1.

Areas of Agreement / Disagreement

Participants express differing views on the treatment of scalars as matrices and the implications for the calculations. There is no consensus on whether H(^T)H can be simplified to I_n without further conditions.

Contextual Notes

Participants note that the assumptions regarding the dimensions of matrices and the nature of scalar multiplication are crucial to the discussion. The relationship between H and P is dependent on the properties of the matrices involved, which may not be fully resolved in the current discussion.

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Problem:

If P is a n x 1 matrix such that P( ^T)*P = 1 and H = I - 2PP(^T), then H(^T)*H is ?

Note :

A(^T) means the transpose of matrix A.

Confusion:

What I don't get is are we supposed to do I (identity matrix-I'm assuming of order 1 x 1) - 2 ? If that is the way we're supposed to do the question then are we supposed to treat 2 as a 1 x 1 matrix. If that's the case then is the following correct:

Since P( ^t)*P = PP(^T) = 1 = [1]

So,

H = I - 2PP(^T) = I - 2PP(^T) = I - 2[1] = [1] - [2] =[-1]

thus,

H(^T)*H = [-1] * [-1](^T) = [-1] * [-1] = [1]


Help?
 
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$$\renewcommand{\vb}[1]{\mathbf{#1}}
\renewcommand{\hb}[1]{\hat{\mathbf{#1}}}$$

If P is a n x 1 matrix such that P( ^T)*P = 1 and H = I - 2PP(^T), then H(^T)*H is ?

If P is nx1, then it is a vector p.
so, switching to LaTeX, we have ##\vb{p}## so that ##\vb{p}^t\vb{p}=1## so it is a unit vector?

##\vb{H}=\vb{I}-2\vb{p}\vb{p}^t##

Then ##\vb{H}^t\vb{H}=?##

So does this translate to 1x1 matrices ... then
##p_{(1\times 1)}=1##, and ##p^tp=1\times 1=1##, and
##H_{(1\times 1)}=I-2p^tp = 1-2=-1## so
##H^tH = (-1)(-1)=1=I_{(1\times 1)}##
... seems reasonable to me so far.
The trick is to articulate your confusion.
The above is consistent with the matrix formulation if ##\vb{H}^t\vb{H}=\vb{I}## for any ##\vb{p}##.

So can you find a ##\vb{p}## so that:
##\vb{H}^t\vb{H}\neq\vb{I}##

... but I suspect the central question is whether it is (or "when is it...") sensible to treat a scalar as a 1x1 matrix.

For instance - you can multiply a nxn matrix by a scalar - but can yout multiply an nxn matrix by a 1x1 matrix?
 
##PP^T## is an n-by-n matrix. (prove: ##P## is n-by-1 and ##P^T## is 1-by-n).

So ##PP^T\neq P^TP## unless if n = 1.

##H## is symmetric.

##H^TH=I_{n}## which has dimension n-by-n.
 
The linear operator you have here is equivalent to

[tex]\underline H(a)=a-2(p \cdot a)p[/tex]

This is a reflection operator, and since it is symmetric, all you have to do is think about what you get when you reflect twice.
 
Reflecting twice off the same "surface" gets you the original vector back.
 
@Simon Bridge, I think you misread the question or made typo part way through your answer. if should be ##H = I - 2pp^t## not ##H = I - 2 p^t p##.

@the OP, as post #3 said, ##pp^T## is symmetric, so ##H## is symmetric. So ##H^T = H##.

To answer the question, you just have to multiply out ##H^T H## = ##H.H## and simplify it using ##P^T P = 1##.

2P means a scalar (2) times a matrix (P). The matrix I has the same dimension as ##P P^T##, which is n by n.
 
Thanks.
 
<sigh> typo - thanks Aleph.
 

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