Sequential Alternating Least Squares (SeALS) MATLAB User’s Guide
نویسندگان
چکیده
This document describes the Sequential Alternating Least Squares (SeALS) tool developed in MATLAB. Five examples are included – scalar unstable system, smooth two dimensional system, an inverted pendulum on a moving cart, a VTOL aircraft, and a quadcopter – to illustrate the use of SeALS. The theoretical background of this tool is given by [1]. The tool is available at [2]. The rest of this document is organized as follow. Section II presents an overview of solving the linear HJB equation using SeALS, and Section III provides detailed descriptions of the MATLAB tool including how to set and use the tool.
منابع مشابه
Software for structured total least squares problems: User’s guide
The package contains ANSI C software with Matlab mex interface for structured total least squares estimation problems. The allowed structures in the data matrix are block-Toeplitz, block-Hankel, unstructured, and noise free. Combinations of blocks with this structures can be specified. The computational complexity of the algorithms is O(m), where m is the sample size.
متن کاملUser’s Guide for TVAL3: TV Minimization by Augmented Lagrangian and Alternating Direction Algorithms
This User’s Guide describes the functionality and basic usage of the Matlab package TVAL3 for total variation minimization. The main algorithm used in TVAL3 is briefly introduced in the appendix.
متن کاملGPS TOOL BOX MILES: MATLAB package for solving Mixed Integer LEast Squares problems
In GNSS, for fixing integer ambiguities and estimating positions, a mixed integer least squares problem has to be solved. The MATLAB package MILES provides fast and numerically reliable routines to solve this problem. In the process of solving a mixed integer least squares problem, an ordinary integer least squares problem is solved. Thus this package can also be used to solve an ordinary integ...
متن کاملA Projected Alternating Least square Approach for Computation of Nonnegative Matrix Factorization
Nonnegative matrix factorization (NMF) is a common method in data mining that have been used in different applications as a dimension reduction, classification or clustering method. Methods in alternating least square (ALS) approach usually used to solve this non-convex minimization problem. At each step of ALS algorithms two convex least square problems should be solved, which causes high com...
متن کاملRegularized Alternating Least Squares Algorithms for Non-negative Matrix/Tensor Factorization
Nonnegative Matrix and Tensor Factorization (NMF/NTF) and Sparse Component Analysis (SCA) have already found many potential applications, especially in multi-way Blind Source Separation (BSS), multi-dimensional data analysis, model reduction and sparse signal/image representations. In this paper we propose a family of the modified Regularized Alternating Least Squares (RALS) algorithms for NMF/...
متن کامل