You can create two-dimensional double and logical matrices using one of two storage
formats: full or sparse. For matrices with mostly zero-valued elements, a sparse matrix
requires a fraction of the storage space required for an equivalent full matrix. Sparse
matrices invoke methods especially tailored to solve sparse problems.These classes require different amounts of storage, the smallest being a logical value
or 8-bit integer which requires only 1 byte. It is important to keep this minimum size in
mind if you work on data in files that were written using a precision smaller than 8 bits.The following table describes the fundamental classes in more detail.Class Name Documentation Intended Use
double, single Floating-Point
Numbers on page
4-7
- Required for fractional numeric data.
- Double on page 4-7 and Single on page 4-7
precision. - Use realmin and realmax to show range of values on
page 4-11. - Two-dimensional arrays can be sparse.
- Default numeric type in MATLAB.
int8, uint8,
int16, uint16,
int32, uint32,
int64, uint64
Integers on page
4-2- Use for signed and unsigned whole numbers.
- More efficient use of memory. on page 29-4
- Use intmin and intmax to show range of values on
page 4-5. - Choose from 4 sizes (8, 16, 32, and 64 bits).
char, string “Characters and
Strings”
- Data type for text.
- Native or Unicode®.
- Converts to/from numeric.
- Use with regular expressions on page 2-41.
- For multiple character arrays, use cell arrays.
- Starting in R2016b, you also can store text in string
arrays. For more information, see string.
Fundamental MATLAB Classes