General Linear Model

Linear Oscillator Model written by Juan Aguirregabiria The Linear Oscillator model solves the harmonic oscillator with or without linear damping and external sinusoidal force. The time evolution and phase space orbit are displayed. Optionally, the evolution of the mechanical energy appears in a...

This is a general purpose controller that I have built using the Fuzzy Logic Rules. You don't need to have any mathematical background in fuzzy logic to run this model.You don't need to have fuzzy logic toolbox to run it aswell.It contains both linear and a nonlinear examples. It also has a read...

This is a learning model for matrix-based data. It can be more efficient than standard vector-based models when the training sample is small or the inputs are matrices, since this model has less parameters than standard ones and exploits an inner structure of the inputs. This model can be...


Platforms: Matlab

The Ejs Duffing Oscillator model computes the solutions to the non-linear Duffing equation, which reads, x'' + 2?zN*x' - x (1 - x2) = f cos(?Ya*t), where each prime denotes a time derivative. The simulation displays the solution as well as the phase space and Poincare plots, and energy diagram....


Platforms: Mac

The Einstein Cannon model computes and displays the trajectory of cannonballs (particles) shot from a cannon in the vicinity of a black hole. It was created for the study of Einstein's theory of general relativity and the Schwarzschild metric. The main window displays a map of space in the...


Platforms: Mac

The Ejs Duffing Phase model computes the solutions to the non-linear Duffing equation, which reads, x'' + 2?zN*x' - x (1 - x2) = f cos(?Ya* t), where each prime denotes a time derivative. The simulation displays the evolution of a group of oscillators with similar initial parameters on a phase...


Platforms: Mac

The Ejs Duffing Chaos model computes the solutions to the non-linear Duffing equation, which reads, x'' + 2?zN*x' - x (1 - x2) = f cos(?Ya* t), where each prime denotes a time derivative. The simulation displays two solutions with different initial positions and a plot of phase. The evolution...


Platforms: Mac

The Ejs Duffing Poincare model computes the solutions to the non-linear Duffing equation, which reads, x'' + 2?zN*x' - x (1 - x2) = f cos(?Ya* t), where each prime denotes a time derivative. The simulation displays the solution Poincare plot. The evolution parameters can be changed via textboxes....


Platforms: Mac

The Ejs Duffing Attractor model computes the solutions to the non-linear Duffing equation, which reads, x'' + 2?zN* x' - x (1 - x2) = f cos(?Ya* t), where each prime denotes a time derivative. The simulation displays a three-dimensional plot of phase space versus angle and three Poincare plots...


Platforms: Mac

Linear Program Solver is a small, simple, very easy to use tool specially designed to help you solve linear programming models. This tool offers: informative solving reports, extended sensitivity analysis, mixed integer models engine. LiPS supports MPS format and simple LP format (like...


Platforms: Windows

function [P R]=Global_Moupfouma(Rzz1,ClimZone)Function implementing the Global Moupfouma model,As per Electronic Letters paper "Point Rainfall rate cumulativedistribution valid at various locations"F. Moupfouma and L. Martin, EL, Vol.29, No.17, Aug. 1993InputsRzz1: Rain rate value exceeded 0.01%...


Platforms: Matlab

This ZIP file contains the nonlinear model of anF-16 fighter aircraft in MATLAB/Simulink, Both high-fidelity and low-fidelity aerodynamic data are available, taken from NASA report 1538 and "Aircraft Control and Simulation" by Lewis & Stevens.A trim function is also included.F16dyn.c and...


Platforms: Matlab

This submission provides the files used in the webinar presentation, "Model-Based Design of Landing Gear".In this presentation, we demonstrate how Model-Based Design (MBD) can be used for the development of flight landing systems. We create and show flight simulations of landings of NASA?s HL20...


Platforms: Matlab

Today safety critical flight control systems are tested using model based approach. The model blocks are proprietary and seldom shared in the open. A benchmark problem was designed as part of a research activity to test out certain test case generation techniques. This model was also used as a...


Platforms: Matlab

The non-linear regression problem (univariate or multivariate) is easily posed using a graphical user interface (GUI) that solves the problem using one of the following solvers: - nlinfit: only univariate problems. - lsqnonlin: can deal with multivariate problems (more than one dependent fitting...


Platforms: Matlab

The reduction of complex linear system is always a very important topic in many courses. In Signal and System it is the analysis of Signal Flow graph(Mason's Rule). In Signal Processing it is to find out the system function from complex filter structure. In Automatic Control it is the reduction...


Platforms: Matlab

In the paper "An estimation technique for Time Indexed gaussian Mixture Models", we propose a model specification that can be used to describe data with spikes, jumps, mean reversion, geometric brownian motion, you name it...We then develop an estimation procedures to extract the parameters from...


Platforms: Matlab

Bayesian Model Averaging for linear models under Zellner's g prior. Options include: fixed (BRIC, UIP, ...) and flexible g priors (Empirical Bayes, hyper-g), 5 kinds of model prior concepts, and model sampling via model enumeration or MCMC samplers (Metropolis-Hastings plain or reversible jump)....


Platforms: Matlab

Let us suppose a set of non-linear equations in the formF(m) = d(m,d are vectors, F is a vector function of vector argument). ANNI tries to construct suitable numerical approximation for inverse projection of d to m, i.e. to find numerical form ofG(d) = m.Such mapping may not exist in general,...


Platforms: Matlab

INPUTS: x - vector row with 'x' values y - vector row with 'y' values r - expected 'x'-coordinate of break point if r is empty it is calculated during the optimisation p - if p is equal to 1 the fit is plotted OUTPUT: th - estimated paremeters of the regression lines y_1 = th(1) + th(2) * x y_2 =...


Platforms: Matlab