Use ss to create real-valued or complex-valued state-space models, or to convert dynamic system models to state-space model form. A state-space model is a mathematical representation of a physical system as a set of input, output, and state variables related by first-order differential equati...
You can create a standard, diffuse, or Bayesian linear or nonlinear state-space model using ssm, dssm, bssm, or bnlssm, respectively. For an overview of supported state-space model forms and to learn how to create a model in MATLAB®, see Create Continuous State-Space Models for Econom...
A state-space model is commonly used for representing a linear time-invariant (LTI) system. It describes a system with a set of first-order differential or difference equations using inputs, outputs, and state variables. In the absence of these equations, a model of a desired order (or num...
Use ss to create real-valued or complex-valued state-space models, or to convert dynamic system models to state-space model form. A state-space model is a mathematical representation of a physical system as a set of input, output, and state variables related by first-order differential equati...
Use idss to create a continuous-time or discrete-time state-space model with identifiable (estimable) coefficients, or to convert Dynamic System Models to state-space form. A state-space model of a system with input vector u, output vector y, and disturbance e takes the following form in co...
State-Space Model Basics What Are State-Space Models? State-space modelsare models that use state variables to describe a system by a set of first-order differential or difference equations, rather than by one or morenth-order differential or difference equations. ...
Usesswith uncertain state-space matrices (umat). For example: p = ureal('p',1); A = [0 3*p; -p p^2]; B = [0; p]; C = ones(2); D = zeros(2,1); usys = ss(A,B,C,D); For another example, seeUncertain State-Space Model. ...
This MATLAB function returns forecasted observations (Y) and their corresponding variances (YMSE) from forecasting the state-space model Mdl using a numPeriods forecast horizon and in-sample observations Y0.
Discrete-time state-space LTV model with 1 outputs, 1 inputs, and 1 states. Model Properties You can set additional properties of the model using dot notation Get ltvSys.InputName = 'u'; ltvSys.OutputName = 'y'; View the data function. Get type ltvFcnDiscrete.m function [A,B,C...
The dssm function returns a dssm object specifying the functional form and storing the parameter values of a diffuse linear Gaussian state-space model for a latent state process xt possibly imperfectly observed through the variable yt. The variables xt and yt can be univariate or multivariate and...