# LMIs in Control/pages/Minimum Singular Value of a Complex Matrix

LMIs in Control/pages/Minimum Singular Value of a Complex Matrix

Minimum Singular Value of a Complex Matrix

## The System

Consider $A\in \mathbb {C} ^{n\times m}$  as well as $\gamma$ . A minimum singular value of a matrix $A$  is greater than $\gamma$  if and only if $AA^{H}>\gamma ^{2}I$  or $A^{H}A>\gamma ^{2}I$ , where $A^{H}$  is the conjugate transpose or Hermitian transpose of the matrix $A$ . the inequality used depends on the size of matrix $A$ .

## The Data

The matrix $A$  is the only data required.

## The LMI: Minimum Singular Value of a Complex Matrix

The following LMIs can be constructed depending on the size of $A$ :

if $A\in \mathbb {C} ^{n\times m}$ , where $n\leq m$ , then:

{\begin{aligned}{\bar {\sigma }}(A)>\gamma \\AA^{H}>\gamma ^{2}I\end{aligned}}

Else if $n\geq m$ , then:

{\begin{aligned}{\bar {\sigma }}(A)>\gamma \\A^{H}A>\gamma ^{2}I\end{aligned}}

## Conclusion:

The results from this LMI will give the maximum complex value of the matrix $A$ :

{\begin{aligned}{\bar {\sigma }}(A)>\gamma \end{aligned}}

This answer can also be proven using the following solution. Note that this solution only works if the matrix $A$  is a square, invertible matrix: $\sigma _{min}=1/||A^{-1}||_{2}$ .

## Implementation

% Minimum Singular Value of Complex Matrix
% -- EXAMPLE --

%Clears all variables
clear; clc; close all;

%SDPVAR variables
gam = sdpvar(1);

%Example Matrix A
A = rand(6,6)+rand(6,6)*1i;

%Constraints
Fc = ( A'*A >= gam*eye(6));

%Objective function
obj=-gam;

%options
opt = sdpsettings('solver','sedumi');

%Optimization
optimize(Fc,obj,opt)

%Displays output
fprintf('\nValue of Min singular value: ')
disp(value(sqrt(gam)))

fprintf('\nMATLAB verified output: ')
disp(1/norm(norm(A^(-1))))