32

您所在的位置：网站首页 › matlab uint32转float › 32

32

2023-05-16 09:07| 来源: 网络整理| 查看: 265

uint32

32-bit unsigned integer arrays

expand all in pageDescription

Variables in MATLAB® of data type (class) uint32 are stored as 4-byte (32-bit) unsigned integers. For example:

y = uint32(10); whos y Name Size Bytes Class Attributes y 1x1 4 uint32

For more information on integer types, see Integers.

Creation

Some array creation functions allow you to specify the data type. For instance, zeros(100,'uint32') creates a 100-by-100 matrix of zeros of type uint32.

If you have an array of a different type, such as double or single, then you can convert that array to an array of type uint32 by using the uint32 function.

SyntaxY = uint32(X)Description

example

Y = uint32(X) converts the values in X to type uint32. Values outside the range [0,232-1] map to the nearest endpoint.

Input Arguments

expand all

X — Input array scalar | vector | matrix | multidimensional array

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

Examples

collapse all

Convert to 32-Bit Unsigned Integer VariableOpen Live Script

Convert a double-precision variable to a 32-bit unsigned integer.

x = 100; xtype = class(x)xtype = 'double' y = uint32(x)y = uint32 100 Extended CapabilitiesTall 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

32

32

今日新闻

推荐新闻