bitcmp
Bit-wise complement
Description
Examples
Complement of a Negative Integer
A = int8(-11); cmp = bitcmp(A)
cmp = int8
10
You can see the complement operation when the numbers are shown in binary.
original = bitget(A,8:-1:1)
original = 1x8 int8 row vector
1 1 1 1 0 1 0 1
complement = bitget(bitcmp(A),8:-1:1)
complement = 1x8 int8 row vector
0 0 0 0 1 0 1 0
Complement of Unsigned Integers
cmp = bitcmp(64,'uint8')
cmp = 191
maxint = intmax('uint8') - 64
maxint = uint8
191
The complement of an unsigned integer is equal to itself subtracted from the maximum integer of its data type.
Input Arguments
A
— Input value
signed integer array | unsigned integer array | double array
Input value, specified as a signed integer array, unsigned integer array, or double array.
If
A
is a double array, andassumedtype
is not specified, then MATLAB® treatsA
as an unsigned 64-bit integer.If
assumedtype
is specified, then all elements inA
must have integer values within the range ofassumedtype
.
Data Types: double
| int8
| int16
| int32
| int64
| uint8
| uint16
| uint32
| uint64
assumedtype
— Assumed data type of A
'uint64'
| 'uint32'
| 'uint16'
| 'uint8'
| 'int64'
| 'int32'
| 'int16'
| 'int8'
Assumed data type of A
, specified as 'uint64'
, 'uint32'
, 'uint16'
, 'uint8'
, 'int64'
, 'int32'
, 'int16'
,
or 'int8'
.
If
A
is a double array, thenassumedtype
can specify any valid integer type, but defaults to'uint64'
.If
A
is an integer type array, thenassumedtype
must specify that same integer type.
Data Types: char
| string
Output Arguments
cmp
— Bit-wise complement
signed integer array | unsigned integer array | double array
Bit-wise complement, returned as a signed integer array, unsigned
integer array, or double array. cmp
is the same
size and type as A
.
Extended Capabilities
C/C++ Code Generation
Generate C and C++ code using MATLAB® Coder™.
GPU Code Generation
Generate CUDA® code for NVIDIA® GPUs using GPU Coder™.
HDL Code Generation
Generate VHDL, Verilog and SystemVerilog code for FPGA and ASIC designs using HDL 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 bitcmp
function
supports GPU array input with these usage notes and limitations:
The input argument
A
must be agpuArray
of unsigned integers.64-bit integers are not supported.
The
assumedtype
argument is not supported.
For more information, see Run MATLAB Functions on a GPU (Parallel Computing Toolbox).
Version History
Introduced before R2006a
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