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From a dynamic programming point of view, Dijkstra's algorithm for the shortest path problem is a successive approximation scheme that solves the dynamic programming functional equation for the shortest path problem by the Reaching method. [7] [8] [9] In fact, Dijkstra's explanation of the logic behind the algorithm, [10] namely Problem 2.
For example, in statistical parsing a dynamic programming algorithm can be used to discover the single most likely context-free derivation (parse) of a string, which is commonly called the "Viterbi parse". [4] [5] [6] Another application is in target tracking, where the track is computed that assigns a maximum likelihood to a sequence of ...
A dynamic programming language is a type of programming language which allows various operations to be determined and executed at runtime. This is different from the compilation phase. Key decisions about variables, method calls, or data types are made when the program is running, unlike in static languages, where the structure and types are ...
In computing, just-in-time (JIT) compilation (also dynamic translation or run-time compilations) [1] is compilation (of computer code) during execution of a program (at run time) rather than before execution. [2] This may consist of source code translation but is more commonly bytecode translation to machine code, which is then executed directly.
Dead-code elimination. In compiler theory, dead-code elimination (DCE, dead-code removal, dead-code stripping, or dead-code strip) is a compiler optimization to remove dead code (code that does not affect the program results). Removing such code has several benefits: it shrinks program size, an important consideration in some contexts, it ...
For the example below, there are four sides: A, B, C and the final result ABC. A is a 10×30 matrix, B is a 30×5 matrix, C is a 5×60 matrix, and the final result is a 10×60 matrix. The regular polygon for this example is a 4-gon, i.e. a square: The matrix product AB is a 10x5 matrix and BC is a 30x60 matrix.
Differential dynamic programming (DDP) is an optimal control algorithm of the trajectory optimization class. The algorithm was introduced in 1966 by Mayne [1] and subsequently analysed in Jacobson and Mayne's eponymous book. [2] The algorithm uses locally-quadratic models of the dynamics and cost functions, and displays quadratic convergence.
v. t. e. C dynamic memory allocation refers to performing manual memory management for dynamic memory allocation in the C programming language via a group of functions in the C standard library, namely malloc, realloc, calloc, aligned_alloc and free. [1][2][3] The C++ programming language includes these functions; however, the operators new and ...