Konrad Zuse built a mechanical computer in 1938 to perform repetitive and cumbersome calculations. Originally, computers were built for numerical and scientific applications.
The use of computers has accelerated the trend as well as enhanced the deployment of numerical libraries and approaches in scientific and engineering communities. This leads to new disciplines and academic interests. These libraries use mathematics and numerical algebraic computations, which contribute to a growing body of research in engineering and computational science. The open source software library is hosted on a GitLab repository.Īlgorithms and scientific computing are workhorses of many numerical libraries that support users to solve technical and scientific problems. The library is implemented and tested on resource-limited IoT as well as on full-fledged operating systems. This module also enables the optimization of the position by performing a method to reduce multipath errors on the mobile device. Furthermore, a positioning module permits computing positions of IoT devices using algorithms for instance trilateration. The open source library also provides optimization methods such as Gauss–Newton and Levenberg–Marquardt algorithms for solving problems of regression smoothing and curve fitting. It enables solving linear and nonlinear equations based on efficient decomposition approaches such as the Singular Value Decomposition (SVD) algorithm.
RcdMathLib also comprises a utilities-module providing sorting and filtering algorithms as well as methods generating random variables. RcdMathLib is modular- and layer-based, whereby different modules allow for algebraic operations such as vector and matrix operations or decompositions. The decentralized processing is a step towards ubiquitous computing enabling the implementation of Internet of Things (IoT) applications. RcdMathLib supports on-the-fly computing on low-cost and resource-constrained devices, e.g., microcontrollers. We developped an open source library called RcdMathLib for solving multivariate linear and nonlinear systems.
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