as shown in picture the author refers it as L2, and later he refers it as H2.
Even the matlab has different functions for H-infinity norm and L-infinity norm. That means that $f'$ has "some discontinuity points" and so $f' \in L^2$. When someone refers 2-norm of system,L2 and H2 are used interchangeably by author and is rather confusing. This example uses norm(x)/sqrt(n) to obtain the root-mean-square (RMS) value of an n-element vector x. Intuitively, functions in $H^1$ are functions that are weakly differentiable, that is they are differentiable everywhere except at a set of points of measure 0. Note that norm(x) is the Euclidean length of a vector x.On the other hand, MATLAB uses 'length' to denote the number of elements n in a vector. Consider an open domain $\Omega$ and a function $f:\Omega \to \mathbb|f(x)|^2 + |f'(x)|^2 dx. To compute the norm of a matrix in Matlab: norm(A,1) norm(A,2)norm(A) norm(A,inf) norm(A,'fro') See below for computation of (the spectral radius of ) Compatible Matrix Norms A matrix can be identified with a linear operator, and the norm of a linear operator is usually defined in the following way. MATLAB and NumPy have a lot in common, but NumPy was created to work with. But for simplicity I will explain the concepts for real valued functions.
NORM MATLAB INSTALL
I am not sure about your application - and we say the $L^2$ norm of a function and not a system. Answer (1 of 2): If you are willing to install YALMIP (a free optimization modeling language for matlab), you can do it very easily as follows (works only for 'p>1') 1) Define your variables (a vector in R2) codex sdpvar(2,1) /code2) Define the ball (e.g., with p 1.5) codeF norm(.
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