acosh
Inverse hyperbolic cosine
Syntax
Description
Examples
Inverse Hyperbolic Cosine of Vector
Find the inverse hyperbolic cosine of the elements of vector X
. The acosh
function acts on X
element-wise.
X = [2 -3 1+2i]; Y = acosh(X)
Y = 1×3 complex
1.3170 + 0.0000i 1.7627 + 3.1416i 1.5286 + 1.1437i
Plot the Inverse Hyperbolic Cosine Function
Plot the inverse hyperbolic cosine function over the interval .
x = 1:0.01:5; plot(x,acosh(x)) grid on xlabel('x') ylabel('acosh(x)')
Input Arguments
X
— Hyperbolic cosine of angle
scalar | vector | matrix | multidimensional array | table | timetable
Hyperbolic cosine of angle, specified as a scalar, vector, matrix, multidimensional
array, table, or timetable. The acosh
operation is element-wise when
X
is nonscalar.
Data Types: single
| double
| table
| timetable
Complex Number Support: Yes
More About
Inverse Hyperbolic Cosine
For real values in the domain , the inverse hyperbolic cosine satisfies
For complex numbers , as well as real values in the domain , the call acosh(z)
returns complex results.
Extended Capabilities
Tall Arrays
Calculate with arrays that have more rows than fit in memory.
The
acosh
function fully supports tall arrays. For more information,
see Tall Arrays.
C/C++ Code Generation
Generate C and C++ code using MATLAB® Coder™.
Usage notes and limitations:
Generates an error during simulation and returns
NaN
in generated code when the input valuex
is real, but the output should be complex. To get the complex result, make the input value complex by passing incomplex(x)
.
GPU Code Generation
Generate CUDA® code for NVIDIA® GPUs using GPU Coder™.
Usage notes and limitations:
Generates an error during simulation and returns
NaN
in generated code when the input valueX
is real, but the output should be complex. To get the complex result, make the input value complex by passing incomplex(X)
.
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 acosh
function
supports GPU array input with these usage notes and limitations:
If the output of the function running on the GPU can be complex, then you must explicitly specify its input arguments as complex. For more information, see Work with Complex Numbers on a GPU (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 R2006aR2023a: Perform calculations directly on tables and timetables
The acosh
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.
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