The `equation-free toolbox' empowers the computer-assisted analysis of complex, multiscale systems. Its aim is to enable you to immediately use microscopic simulators to perform macro-scale system level tasks and analysis, because micro-scale simulations are often the best available description of a system. The methodology bypasses the derivation of macroscopic evolution equations by computing the micro-scale simulator only over short bursts in time on small patches in space, with bursts and patches well-separated in time and space respectively. We introduce the suite of coded equation-free functions in an accessible way, link to more detailed descriptions, discuss their mathematical support, and introduce a novel and efficient algorithm for Projective Integration. Some facets of toolbox development of equation-free functions are then detailed. Download the toolbox functions (https://github.com/uoa1184615/EquationFreeGit) and use to empower efficient and accurate simulation in a wide range of your science and engineering problems.
Matlab has been considered as a leader computational platform for many engineering fields. Well documented and reliable, Matlab presents as a great advantage its ability to increase the user productivity. However, Python and Octave are among some of the languages that have challenged Matlab. Octave and Python are well known examples of high-level scripting languages, with a great advantage of being open source software. The novelty of this paper is devoted to offer a comparison among these tree languages in the simulation of dynamical systems. We have applied the lower bound error to estimate …
This paper presents a Matlab toolbox to perform basic image processing and visualization tasks, particularly designed for medical image processing. The functionalities available are similar to basic functions found in other non-Matlab widely used libraries such as the Insight Toolkit (ITK). The toolbox is entirely written in native Matlab code, but is fast and flexible. Main use cases for the toolbox are illustrated here, including image input/output, pre-processing, filtering, image registration and visualisation. Both the code and sample data are made publicly available and open source.
For the approximation and simulation of twofold iterated stochastic integrals and the corresponding Lévy areas w.r.t. a multi-dimensional Wiener process, we review four algorithms based on a Fourier series approach. Especially, the very efficient algorithm due to Wiktorsson and a newly proposed algorithm due to Mrongowius and Rössler are considered. To put recent advances into context, we analyse the four Fourier-based algorithms in a unified framework to highlight differences and similarities in their derivation. A comparison of theoretical properties is complemented by a numerical simulation…
SPSMAT (Spectral/Pseudospectral matrix method) is an add-on for Octave, that helps you solve nonfractional-/fractional ordinary/partial differential/integral equations. In this version, as the first version, the well-defined spectral or pseudospectral algorithms are considered to solve differential and integral equations. The motivation is that there are few software packages available that make such methods easy to use for practitioners in the field of scientific computing. Additionally, one of the most practical platforms in computation, MATLAB, is currently not supporting beneficial and fre…
In several research problems we deal with probabilistic sequences of inputs (e.g., sequence of stimuli) from which an agent generates a corresponding sequence of responses and it is of interest to model the relation between them. A new class of stochastic processes, namely \textit{sequences of random objects driven by context tree models}, has been introduced to model such relation in the context of auditory statistical learning. This paper introduces a freely available Matlab toolbox (SeqROCTM) that implements this new class of stochastic processes and three model selection procedures to make…
MatConvNet is an implementation of Convolutional Neural Networks (CNNs) for MATLAB. The toolbox is designed with an emphasis on simplicity and flexibility. It exposes the building blocks of CNNs as easy-to-use MATLAB functions, providing routines for computing linear convolutions with filter banks, feature pooling, and many more. In this manner, MatConvNet allows fast prototyping of new CNN architectures; at the same time, it supports efficient computation on CPU and GPU allowing to train complex models on large datasets such as ImageNet ILSVRC. This document provides an overview of CNNs and h…
The Intel Xeon Phi manycore processor is designed to provide high performance matrix computations of the type often performed in data analysis. Common data analysis environments include Matlab, GNU Octave, Julia, Python, and R. Achieving optimal performance of matrix operations within data analysis environments requires tuning the Xeon Phi OpenMP settings, process pinning, and memory modes. This paper describes matrix multiplication performance results for Matlab and GNU Octave over a variety of combinations of process counts and OpenMP threads and Xeon Phi memory modes. These results indicate…
Institute for Computational and Applied Mathematics（计算与应用数学研究所）；Cells in Motion Cluster of Excellence（细胞运动卓越集群）；University of Münster（明斯特大学）
\textbf{FlexBox} is a flexible MATLAB toolbox for finite dimensional convex variational problems in image processing and beyond. Such problems often consist of non-differentiable parts and involve linear operators. The toolbox uses a primal-dual scheme to avoid (computationally) inefficient operator inversion and to get reliable error estimates. From the user-side, \textbf{FlexBox} expects the primal formulation of the problem, automatically decouples operators and dualizes the problem. For large-scale problems, \textbf{FlexBox} also comes with a \cpp-module, which can be used stand-alone or t…
Bayesian Modeling with Gaussian Processes using the GPstuff Toolbox
Aalto University（阿尔托大学）；University of Helsinki（赫尔辛基大学）；Helsinki Institute for Information Technology HIIT（赫尔辛基信息技术研究所（HIIT））；Aalto University School of Science（阿尔托大学理学院）
