linear-bounded automata

Linear-bounded automata (LBA) are theoretical machines used in computer science to recognize certain types of languages. They work similarly to Turing machines but have a limited amount of memory, specifically proportional to the length of the input they receive. This means they can only use a specific amount of tape for computation, making them more constrained. LBAs can precisely recognize context-sensitive languages, which are more complex than those understood by simpler machines, like finite automata, but less complex than those handled by unrestricted Turing machines. They are essential for understanding the limits of computation within specific boundaries.