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Questions tagged [positive-semidefinite]

Relating to a symmetric $n\times n $ real matrix $(M)$ such that the scalar $x^TMx\ge 0\ \forall x\in \Bbb{R}^n\backslash \{0\}$

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1answer
25 views

Inequality w.r.t determinant of a non-negative definite matrix.

I am reading a paper where the author mentioned the following property without proof. Neither can I prove it nor can I find the proof in various textbooks. For any non-negative definite (i.e. ...
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2answers
30 views

Numerically verify a matrix is positive semidefinite

I am trying to numerically (in Julia) verify that A symmetric matrix $\mathbf{A}$ is positive semidefinite if and only if it is a covariance matrix. Then I need to verify in both directions, i.e. ...
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2answers
48k views

What is the proof that covariance matrices are always semi-definite?

Suppose that we have two different discreet signal vectors of $N^\text{th}$ dimension, namely $\mathbf{x}[i]$ and $\mathbf{y}[i]$, each one having a total of $M$ set of samples/vectors. $\mathbf{x}[m]...
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0answers
88 views

equivalent definition of positive semidefinite matrix

A matrix $M$ is positive semidefinite if and only if $y^T M y \geq 0$ for all possible $y$. We can also show that $M \succeq 0$ if and only if $[\bar{y}^T,1 ]M[\bar{y}^T,1]^T \geq 0$ for all possible ...
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Can this matrix be negative definite?

Let $d = 12$ and $m = 6$, and denote by $0_n$ and $I_n$ the zero matrix and the identity matrix of size $n \times n$. Let $D_+ \in \mathbb{R}^{m \times m}$ be a diagonal matrix with positive ...
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1answer
16 views

Positive trace (all diagonal entries are positive) implies semipositive definite?

I am working on a matrix with all the diagonal entries are strictly positive while every other entry is strictly negative. This matrix is symmetric as well. I want to show that this matrix is ...
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0answers
19 views

Monotonicity of matrix inverse of positive definite matrices [duplicate]

If $A$ and $B$ are positive definite, $A-B$ is positive definite, can we say $B^{-1}-A^{-1}$ is positive definite? I think this should be true but I don't know how to prove it. It would be great if ...
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62 views

Semidefinite optimization

I'm a physicist and I'm working on a problem that can be reduced to a SDP problem. My problem is: is there a theorem that assures that the result of an optimization saturates the constraint instead of ...
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4answers
53 views

How to show that this matrix is positive semidefinite?

Using the definition, show that the following matrix is positive semidefinite. $$\begin{pmatrix} 2 & -2 & 0\\ -2 & 2 & 0\\ 0 & 0 & 15\end{pmatrix}$$ In other words, if ...
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0answers
37 views

Find a counter example to majorization theory

Theorem: Let $X$ be an $n\times n$ positive semi-definite Hermitian matrix with diagonal elements $d=[d_1\cdots d_n]'$ and eigenvalues $\lambda=[\lambda_1\cdots\lambda_n]'$, where $d_1\geq\cdots\geq ...
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5answers
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Intuitive explanation of a positive semidefinite matrix

What is an intuitive explanation of a positive-semidefinite matrix? Or a simple example which gives more intuition for it rather than the bare definition. Say $x$ is some vector in space and $M$ is ...
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1answer
33 views

Positivity of a matrix

Let $A$ be a $3\times 3$ matrix defined in the following way: $$A=\begin{bmatrix} a & c & 0\\c & b &-c\\0 & -c & 1-a-b\end{bmatrix}$$ I wish to show that $A=BB^t$ for some ...
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1answer
36 views

How to simplify this trace term?

I have the following trace term: trace(Sk' Ck Sk) where Sk is a KxM matrix and Ck is a KxK positive semidefinite matrix. I'm involving this trace term in a ...
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0answers
23 views

Proving that the difference of two matrices is positive semi-definite

I would like some hint to show that the following matrix is positive semi-definite. Thanks for any help in advance. $(\text{X}^{T} \Omega^{-1}\text{X})^{-1}\text{X}^{T}\Omega^{-1}\Omega^{-1}\text{X}(\...
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1answer
57 views

Determinant of a positive semi-definite matrix

If $M$ is a Hermitian matrix, then $M$ is positive definite if and only if its leading principal minors have positive determinant, i.e the following matrices have positive determinant: The upper-left ...
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2answers
89 views

Parametrization of unitary matrices

Does anyone know a simple way to parametrize the space of $n\times n$ complex unitary matrices into a set of independent complex numbers in some complex-rectangle? Specifically the mapping and inverse ...
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0answers
30 views

Can eigenvalues of a correlation matrix be negative?

Can eigenvalues of a correlation matrix be negative? I am a bit confused because I know that a correlatin matrix $C$ is always positive semi-definite ie for all $v \in \mathbb R^n$ we have $v^T C v \...
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1answer
61 views

Easiest way to show positive semi-definite equivalence

For an $x \in \mathbb{R}^n$, and $n$-by-$n$ identity matrix $I_n$, we are given that $$ \begin{pmatrix} I_n & x \\ x^T & 1 \end{pmatrix} \succeq 0.$$ What is the easiest way to show that $$ \...
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0answers
13 views

Absolute convex hull of rank 1-correlation matrices?

Does there exist a ''universal'' constant, $c > 0$ say, such that for any(!) $k \in \mathbb{N}$ every(!) $k \times k$-correlation matrix $\Sigma$ can be written as $\Sigma = c\Theta$, where $\Theta$...
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1answer
691 views

What do negative eigenvalues for Laplacian matrix, if possible, represent?

I created a Laplacian matrix for data points, which is $L = D - A$, and when I do compute the eigenvalues of $L$, I sometimes get a negative eigenvalue. I know that for nonlinear dimensionality ...
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2answers
45 views

Proving the difference of two matrices is PSD

Claim: For $x\in \mathbb{R}^n$, we have $\operatorname{Diag}(x) - xx^T \succeq 0$ if and only if $x_i \geq 0 \ \forall i\in [n]$ and $\sum_{i} x_i \leq 1$. Where $\operatorname{Diag}$ denotes the ...
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2answers
127 views

Is a square zero matrix positive semidefinite?

Does the fact that a square zero matrix contains non-negative eigenvalues (zeros) make it proper to say it is positive semidefinite?
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1answer
14 views

Negating off-diagonal blocks retains positive-semidefiniteness?

I am trying to follow some notes that state $$ M= \begin{bmatrix} A&B^T\\B&C \end{bmatrix} \succeq 0 \Longleftrightarrow M'= \begin{bmatrix} A&-B^T\\-B&C \end{bmatrix} \succeq 0$$ and ...
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1answer
102 views

How to prove the logistic loss function is strongly convex?

The logistic loss function is: $$\mathcal{L}=\frac{1}{n}\sum_{i=1}^n\log(1+\exp(-y_ix_i^T\theta))$$ in which $y_i\in\{-1,+1\},x\in \mathbb{R}^d$. How to show that $\mathcal{L}$ is strongly convex. My ...
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1answer
22 views

Nearest positive semi definite matrix to a complex valued Hermitian matrix

How would you find the nearest (via Hilbert distance), PSD matrix (with trace = 1) to a Hermitian matrix? I found an answer to a similar question here. However, as I understand, Hingham's work only ...
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2answers
44 views

If both $A-B$ and $B-A$ are positive semidefinite, then $A = B$

Let $A, B$ be two positive semidefinite matrices. Prove that if both $A-B$ and $B-A$ are positive semidefinite, then $A = B$. I can show that their diagonal elements are the same but for others I ...
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0answers
29 views

Non-Negative Vs Positive Semi Definite

A matrix is PSD if $$\langle Ax, x\rangle \ge 0, \forall x \in H$$ Where, H is a hilbert space and A is a mapping $H \rightarrow H$. Is it the same as being Non-negative? I couldn't seem to find a ...
3
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1answer
59 views

Matrices Inequality Proof

Recently, I read a paper and there is a step which turns out not obvious to me. The statement is as follows: All matrices here are real matrices. $F$ is an arbitrary square matrix. $\Psi$ is a ...
4
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1answer
173 views

Differentiability of the Schatten $p$-norm on positive definite matrices

Let $V$ be the vector space of symmetric matrices in $\Bbb R^{n\times n}$. For $p\in (1,\infty)$, the Schatten $p$-norm of $M\in V$ is defined as $\|M\|_p =(\sum_{i=1}^n \sigma_i(M)^p)^{1/p}$ where $\...
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Semidefinite Matrix in LINGO

Using LINGO, I need to enter the following block matrix as one of my constraints $ M= \left[ {\begin{array}{cc} 1 & x^T \\ x & X \\ \end{array} } \right] $ where x is an n by 1 ...
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2answers
33 views

Sum of symmetric, positive semidefinite matrices

Let $A \in \mathbb{R}^{m \times n}, B \in \mathbb{R}^{p \times n}$. Show that $A^{T}A+ B^{T}B$ is invertible if and only if $\ker A \cap \ker B =\lbrace 0 \rbrace$. I could show that if it's ...
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0answers
28 views

Why would sequential quadratic programming fail to find global minimum?

I have a data set. A matrix $X$, $1300 \times 20$ and output vector $\mathbf{y} \in \Bbb R^{20}$ $$\mathbf{y} = \begin{bmatrix} 100\\100\\\vdots\\100\end{bmatrix}$$ I am trying to run OLS on this ...
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1answer
15 views

Explanation on how a matrix $A$ expressed as a product involving a positive semidefinite matrix $\mathcal{H}$ is also positive semidefinite

Suppose we know that that a Hermitian $n \times n$ matrix $A$ can be expressed as the following matrix product $$A = \begin{bmatrix} z_1 & 0 & ... & 0 \\ 0 & z_2 & ... &...
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2answers
72 views

How to prove that a function is non-negative definite?

The function I am trying to prove is $\exp(-2\lvert j-k\rvert)$. Here is what I have tried; $\sum_{j=1}^n \sum_{k=1}^n\ a_j \bar{a_k}\exp(-2\lvert j-k\rvert)$ =$\sum_{j=1}^n \sum_{k=1}^n\ a_j \bar{...
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1answer
45 views

Sufficient conditions for Loewner ordering of two matrices?

Le $\mathbf{A}$ and $\mathbf{B}$ two psd matrices of size $n$. Additionally we assume that the entries are real and non-negative. Does the following hold: $$\forall (i,j) \in [n], \mathbf{A}_{ij} \leq ...
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0answers
18 views

Product of a positive semi definite matrix with an indefinite matrix

I see from my examples that the product of a positive semidefinite matrix(graph Laplacian) and an indefinite matrix (real matrices), comes to be a positive semidefinite matrix. Is there a proof for ...
2
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1answer
28 views

Intuitions about positive definite functions

I am looking for further intuitions about positive definite functions, and have several related questions on this matter. I know this isn't the most specific question, but I find that speaking ...
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0answers
42 views

Minimum of $\langle Ax,x \rangle - 2 \langle b,x \rangle$.

In exercise 5 of section 0 of Fundamentals of convex analysis by Hiriart-Urrut, Lemaréchal, we're supposed to prove that if a self-adjoint linear operator $A:\mathbb{R}^n \rightarrow \mathbb{R}^n$ is ...
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2answers
2k views

Singularity positive semidefinite

The determinant of a matrix equals the product of its eigenvalues. A positive semidefinite matrix is a symmetric matrix with only nonnegative eigenvalues. A positive definite matrix is a symmetric ...
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0answers
18 views

Inverse of $(rP+\bar{r}\bar{P})$ where $P=P^*$ and $r=\exp(i\theta)$

I have a positive definite Hermitian matrix $P=P^*>0$ where $P^*$ is the conjugate transpose of $P$ and $r=\exp(i\theta)$. So, how can I prove that $$ (rP+\bar{r}\bar{P})^{-1}=rY+\bar{r}\bar{Y}$$ ...
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1answer
32 views

Positive definite matrix properties

I am having trouble solving a property that I found. If $A:n \times n$ is defined as a positive definite matrix and $B: n \times m$ where $rank(B) = r$. Then $B^T A B > 0$, only when r = m and $B^...
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0answers
49 views

Determinant of Hadamard product / sum of matrices (one diagonal)

I am trying to compute the determinant of $\boldsymbol{W}\odot \boldsymbol{S}$, where $\boldsymbol{S} \in PD(p)$ positive semidefinite matrix and $\boldsymbol{W}$ is a matrix whose diagonal entries $...
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1answer
26 views

Clarification wrt proof for linear regression cost function being convex

I have trouble understanding the proof which computes hessian of J to see if the optimisation problem is convex. why is the least square cost function for linear regression convex The proof claims ...
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2answers
85 views

What is the Hessian of the spectral norm?

The spectral norm of a symmetric matrix is the absolute value of the top eigenvalue. The gradient of this norm is $uu^T$ where $u$ is the eigenvector associated with that top eigenvalue. Assume that $...
2
votes
1answer
58 views

showing that map $f$ is positive

Prove that $f: x \to Tx$ is positive on $\mathbb{C}^n$ iff $T$ has ony non-negative eigen values, for a complex $n\times n$ Hermitian matrix $T$. To prove that $f$ is positive I need to show that $\...
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1answer
42 views

The positive semi-definiteness of the element-wise matrix product

I understand that if two matrices are PSD, then the element-wise product of the two matrices is also PSD. However if a matrix in the form $K = A \odot B$ is PSD for any PSD matrix $A$. How about $B$? ...
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0answers
46 views

Is sum of inverse of max a kernel?

For $X$ be a nonempty set, a function $f :X\times X\to\mathbb R$ is called a kernel on $X$ if for all $m\in \mathbb N$ and all $x_1,\cdots,x_m \in X$ $$K_f\equiv\begin{bmatrix} f(x_1,x_1) & \cdots ...
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1answer
113 views

If $M\geq 0$, why $M$ is invertible if and only if $\left< Mv, v \right> = 0$ implies that $v = 0$?

Let $\mathcal{B}(F)$ the algebra of all bounded linear operators on a complex finite dimensional Hilbert space $F$. Let $M\in \mathcal{B}(F)^+$ (i.e. $\langle Mx\;, \;x\rangle\geq 0$ for all $x\in F$. ...
2
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1answer
35 views

Optimizing over vector and Matrix at the same time.

I want to know if my understand (prove convexity, format as SDP) the following problem is correct: \begin{equation*} \begin{aligned} & \min_{c\in \mathbb{C}^n,D\in \mathbb{H}_+^n} && \|c\|...
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3answers
198 views

How to prove Rank(A+B)$\ge$max{Rank(A),Rank(B)} for positive semi-definite A and B

How to prove $\text{Rank}(A+B)\ge\max(\text{Rank}(A),\text{Rank}(B))$ if $A\in S_+^n$ and $B\in S_+^n$ (i.e. $A$ and $B$ are both $n\times n$ symmetry positive semi-positive matrices)?