Create a vector, then compute the differences between the elements.

X = [1 1 2 3 5 8 13 21];
Y = diff(X)

Y = 1×7

     0     1     1     2     3     5     8

Note that Y has one fewer element than X.

Create a 3-by-3 matrix, then compute the first difference between the rows.

X = [1 1 1; 5 5 5; 25 25 25];
Y = diff(X)

Y = 2×3

     4     4     4
    20    20    20

Y is a 2-by-3 matrix.

Create a vector and compute the second-order difference between the elements.

X = [0 5 15 30 50 75 105];
Y = diff(X,2)

Y = 1×5

     5     5     5     5     5

Create a 3-by-3 matrix, then compute the first-order difference between the columns.

X = [1 3 5;7 11 13;17 19 23];
Y = diff(X,1,2)

Y = 3×2

     2     2
     4     2
     2     4

Y is a 3-by-2 matrix.

Use the diff function to approximate partial derivatives with the syntax Y = diff(f)/h, where f is a vector of function values evaluated over some domain, X, and h is an appropriate step size.

For example, the first derivative of sin(x) with respect to x is cos(x), and the second derivative with respect to x is -sin(x). You can use diff to approximate these derivatives.

h = 0.001;       % step size
X = -pi:h:pi;    % domain
f = sin(X);      % range
Y = diff(f)/h;   % first derivative
Z = diff(Y)/h;   % second derivative
plot(X(:,1:length(Y)),Y,'r',X,f,'b', X(:,1:length(Z)),Z,'k')

In this plot the blue line corresponds to the original function, sin. The red line corresponds to the calculated first derivative, cos, and the black line corresponds to the calculated second derivative, -sin.

Create a sequence of equally-spaced datetime values, and find the time differences between them.

t1 = datetime('now');
t2 = t1 + minutes(5);
t = t1:minutes(1.5):t2

t = 1x4 datetime
Columns 1 through 3

   17-Aug-2020 15:41:10   17-Aug-2020 15:42:40   17-Aug-2020 15:44:10

Column 4

   17-Aug-2020 15:45:40

dt = diff(t)

dt = 1x3 duration
   00:01:30   00:01:30   00:01:30

diff returns a duration array.