abs
Absolute value and complex magnitude
Syntax
Description
Y = abs(
returns
the absolute value of
each element in array X
)X
.
If X
is complex, abs(X)
returns
the complex magnitude.
Examples
Absolute Value of Scalar
Absolute Value of Vector
Create a numeric vector of real values.
x = [1.3 -3.56 8.23 -5 -0.01]'
x = 5×1
1.3000
-3.5600
8.2300
-5.0000
-0.0100
Find the absolute value of the elements of the vector.
y = abs(x)
y = 5×1
1.3000
3.5600
8.2300
5.0000
0.0100
Magnitude of Complex Number
Input Arguments
X
— Input array
scalar | vector | matrix | multidimensional array
Input array, specified as a scalar, vector, matrix, or multidimensional
array. If X
is complex, then it must be a single
or double
array.
The size and data type of the output array is the same as the input
array.
Data Types: single
| double
| int8
| int16
| int32
| int64
| uint8
| uint16
| uint32
| uint64
| duration
More About
Absolute Value
The absolute value (or modulus) of a real number is the corresponding nonnegative value that disregards the sign.
For a real value, a
, the absolute value is:
a
, ifa
is greater than or equal to zero-a
, ifa
is less than zero
abs(-0)
returns 0
.
Complex Magnitude
The complex magnitude (or modulus) is the length of a vector from the origin to a complex value plotted in the complex plane.
For a complex value, is defined as .
Extended Capabilities
Tall Arrays
Calculate with arrays that have more rows than fit in memory.
This 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™.
This function fully supports GPU arrays. 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
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