Learn how MATLAB can simplify and speed up some common steps of AI algorithm design, implementation, and deployment.

Learn how to develop efficient and effective algorithms for operations research with MATLAB. Follow best practices and tips for choosing, testing, improving, and deploying algorithms.

The MathWorks has speeded up the code generation capability of its flagship Matlab algorithm development tool by up to 160 times, using a speculative-compilation approach, writes Nick Flaherty. By ...

This paper presents the architecture and modeling approach of a Matlab-based toolbox for developing and testing home energy management (HEM) algorithms under a number of typical operation conditions.

NATICK, Mass., October 1, 2007 – MATLAB users can now generate embeddable C code from M-files using Embedded MATLAB, a subset of the MATLAB programming language. Embedded MATLAB supports a wide range ...

The development of a stable PID algorithm, the integration of RC and SPI protocols, and the use of Matlab/Simulink for performance optimization were key achievements that contributed to the project's ...

Historically, exploiting FPGA or ASIC implementation of DSP algorithms has been the domain of companies with highly-skilled designers and large budgets. Now, a new generation of tools is bringing ...

The representation of genetic programs (parse trees) Genetic operators including natural selection, reproduction, and mutation An easy-to-use programming framework to build and train your GP models A ...

MATLAB Coder supports an extensive set of MATLAB language features for algorithm development, including built-in matrix math operators and dynamic array handling. Hundreds of operators, functions, and ...

Scientific Computing relies on executing computer algorithms coded in some programming languages. Given a particular available hardware, algorithms speed is a crucial factor. There are many scientific ...