exp

Exponential

Syntax

Y = exp(X)

Description

Y = exp(X) returns the exponential e^x for each element in array X. For complex elements z = x + iy, it returns the complex exponential

$$e^z=e^x\left(\cos y+i\sin y\right).$$

Use expm to compute a matrix exponential.

Examples

Numeric Representation of e

Calculate the exponential of 1, which is Euler's number, e.

exp(1)

ans = 
2.7183

Euler's Identity

Euler's identity is the equality $$e^{i\pi }+1=0$$.

Compute the value of $$e^{i\pi }$$.

Y = exp(1i*pi)

Y = 
-1.0000 + 0.0000i

Plot Exponential Function

Plot $$y=e^{x/2}$$ for x values in the range $$[-2,10]$$.

X = -2:0.5:10;
Y = exp(X/2);
plot(X,Y)

Input Arguments

X — Input array

scalar | vector | matrix | multidimensional array | table | timetable

Input array, specified as a scalar, vector, matrix, multidimensional array, table, or timetable.

Data Types: single | double | table | timetable
Complex Number Support: Yes

Output Arguments

Y — Exponential values

scalar | vector | matrix | multidimensional array | table | timetable

Exponential values, returned as a scalar, vector, matrix, multidimensional array, table, or timetable.

For real values of X in the interval (-Inf, Inf), Y is in the interval (0,Inf). For complex values of X, Y is complex. The data type of Y is the same as that of X.

Extended Capabilities

Tall Arrays

Calculate with arrays that have more rows than fit in memory.

The exp function fully supports tall arrays. For more information, see Tall Arrays.

C/C++ Code Generation
Generate C and C++ code using MATLAB® Coder™.

GPU Code Generation
Generate CUDA® code for NVIDIA® GPUs using GPU Coder™.

Thread-Based Environment

Run code in the background using MATLAB® backgroundPool or accelerate code with Parallel Computing Toolbox™ ThreadPool.

This function fully supports thread-based environments. For more information, see Run MATLAB Functions in Thread-Based Environment.

GPU Arrays

Accelerate code by running on a graphics processing unit (GPU) using Parallel Computing Toolbox™.

The exp function fully supports GPU arrays. To run the function on a GPU, specify the input data as a gpuArray (Parallel Computing Toolbox). For more information, see Run MATLAB Functions on a GPU (Parallel Computing Toolbox).

Distributed Arrays

Partition large arrays across the combined memory of your cluster using Parallel Computing Toolbox™.

This function fully supports distributed arrays. For more information, see Run MATLAB Functions with Distributed Arrays (Parallel Computing Toolbox).

Version History

Introduced before R2006a

R2023a: Perform calculations directly on tables and timetables

The exp function can calculate on all variables within a table or timetable without indexing to access those variables. All variables must have data types that support the calculation. For more information, see Direct Calculations on Tables and Timetables.