Numeric Types

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Integer and floating-point data

Numeric classes in MATLAB^® include signed and unsigned integers, and single-precision and double-precision floating-point numbers. By default, MATLAB stores all numeric values as double-precision floating point. (You cannot change the default type and precision.) You can choose to store any number, or array of numbers, as integers or as single-precision. Integer and single precision arrays offer more memory-efficient storage than double precision.

All numeric types support basic array operations, such as indexing, reshaping, and mathematical operations.

Functions

Create Numeric Variables

`double`	Double-precision arrays
`single`	Single-precision arrays
`int8`	8-bit signed integer arrays
`int16`	16-bit signed integer arrays
`int32`	32-bit signed integer arrays
`int64`	64-bit signed integer arrays
`uint8`	8-bit unsigned integer arrays
`uint16`	16-bit unsigned integer arrays
`uint32`	32-bit unsigned integer arrays
`uint64`	64-bit unsigned integer arrays

Convert Between Numeric Types

`cast`	Convert variable to different data type
`typecast`	Convert data type without changing underlying data

Query Type and Value

`isinteger`	Determine whether input is integer array
`isfloat`	Determine if input is floating-point array
`isnumeric`	Determine whether input is numeric array
`isreal`	Determine whether array is real
`isfinite`	Determine which array elements are finite
`isinf`	Determine which array elements are infinite
`isnan`	Determine which array elements are NaN

Numeric Value Limits

`eps`	Floating-point relative accuracy
`flintmax`	Largest consecutive integer in floating-point format
`Inf`	Create array of all `Inf` values
`intmax`	Largest value of specific integer type
`intmin`	Smallest value of specified integer type
`NaN`	Create array of all `NaN` values
`realmax`	Largest positive floating-point number
`realmin`	Smallest normalized floating-point number

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