# Generalised stochastic petrinets

The following C project contains the C source code and C examples used for generalised stochastic petrinets. this program manages evalute the performances by using stochastic petrinets.

The following Matlab project contains the source code and Matlab examples used for nonlinear least square optimization through parameter estimation using the unscented kalman filter.
The Kalman filter can be interpreted as a feedback approach to minimize the least equare error.

The following Matlab project contains the source code and Matlab examples used for exact negative log likelihood of arma models via kalman filtering.
Several functions for evaluating the exact negative log-likelihood of ARMA models in O(n) time using the Kalman Filter.

The following Matlab project contains the source code and Matlab examples used for measurement fusion & state vector fusion.
3D target tracking using fusion of IR and radar measurements. Measurement fusion and state vector fusion along with extended Kalman filter. Run the demo.m to see the results.

The following Matlab project contains the source code and Matlab examples used for unscented kalman filter (ukf) modeling of fitzhugh nagumo dynamics.
Unscented Kalman Filter (UKF) applied to FitzHugh-Nagumo neuron dynamics.

The following Matlab project contains the source code and Matlab examples used for gui for denoising video signals with kalman filter.
Denoising grayscale video signals using :
1) Estimation with windows option : 3x3x3 or 3x3x2
2) Kalman filter
Note :
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1.

The following Matlab project contains the source code and Matlab examples used for ekf slam example.
To Run: EKFSLAM
By SRAU

The following Matlab project contains the source code and Matlab examples used for extend kalman filter for damage detection in large scale structure.
to calculate the responses: run cal.m
for system identification, run substructure1/substructure2.m

The following Matlab project contains the source code and Matlab examples used for function evaluatealphabetaparam evaluates alpha and beta parameters for alpha-beta filter .
This function evaluates alpha and beta parameters for alpha-beta filter so that the alpha-beta filter becomes a steady-state Kalman filter.

The following Matlab project contains the source code and Matlab examples used for function evalabgparam evaluates the best stable values for an alpha-beta-gamma filter .
This function evaluates alpha, beta and gamma parameters and also test its stability. These parameters can make alpha-beta-gamma filter act like a steady-state Kalman filter.

The following Matlab project contains the source code and Matlab examples used for kalman filter square root covariance update.
This file compares three different versions of the Kalman filter.

The following Matlab project contains the source code and Matlab examples used for inverse dynamics of a 2 link rr planar parallel manipulator.
I have created a function which calculates the 3 main torque components that contribute to the total torque profile of the actuated joints using Lagrangian formulation.

The following Matlab project contains the source code and Matlab examples used for multi channel physiological signal estimation (physionet 2010 challenge entry).
Combination of gradient adaptive laguerre lattice filters and Kalman filter for the estimation of a missing signal in a multichannel record.

Particle filters or Sequential Monte Carlo (SMC) methods are a set of on-line posterior density estimation algorithms that estimate the posterior density of the state-space by directly implementing the Bayesian recursion equations.

The following matlab project contains the source code and matlab examples used for particle filter.

The following Matlab project contains the source code and Matlab examples used for particle filter comparison with smoothing methods.
This program simulates a nonlinear dynamical system and estimates the hidden state using particle methods.

The following Matlab project contains the source code and Matlab examples used for particle filter tutorial.
This file implements the particle filter described in
Arulampalam et. al. (2002). A tutorial on particle filters for online nonlinear/non-gaussian bayesian tracking. IEEE Transactions on Signal Processing. 50 (2). p 174--188
Heavily commented code included

The following Matlab project contains the source code and Matlab examples used for tracking of a point in video using kalman filter.
Tracking of a red point in video which is moving according the parametric equation of Astroid using 5 equations of Kalman Filter.

The following Matlab project contains the source code and Matlab examples used for extended kalman filter tracking object in 3 d.
Assume that we want to track an object moving in 3-D space with constant velocity.

The following Matlab project contains the source code and Matlab examples used for object tracking with an iterative extended kalman filter (iekf).
This is my Matlab implementation of Ted Broida's "Estimation of Object Motion
Parameters from Noisy Images.

The following Matlab project contains the source code and Matlab examples used for used background subtraction and kalman filter for moving object tracking .
The red bounding box indicates the background subtraction result and green one indicates the kalman filter result

The following Matlab project contains the source code and Matlab examples used for neural network training using the unscented kalman filter.
Similar to using the extended Kalman filter, Neural Networks can also be trained through parameter estimation using the unscented Kalman filter.

The following Matlab project contains the source code and Matlab examples used for neural network training using the extended kalman filter.
The extended Kalman filter can not only estimate states of nonlinear dynamic systems from noisy measurements but also can be used to estimate parameters of a nonlinear system.

Kalman filter is an algorithm that uses a series of measurements observed over time, containing noise (random variations) and other inaccuracies, and produces estimates of unknown variables that tend to be more precise than those based on a single measurement alone.

The following Matlab project contains the source code and Matlab examples used for kalman voltage.
This is a small voltage measurement example to understand Kalman filter.

The following Matlab project contains the source code and Matlab examples used for kalman filter simlation with singer model.
Kalman filter simlation with Singer model. It displays the estimated and predicted errors and results.

The following Matlab project contains the source code and Matlab examples used for unconstrained optimization using the extended kalman filter.
The Kalman filter is actually a feedback approach to minimize the estimation error in terms of sum of square.

The following Matlab project contains the source code and Matlab examples used for dual extended kalman filter (dekf).
The package implements Dual Extended Kalman Filter function for the application of time-varying MVAR parameter estimation.

The following Matlab project contains the source code and Matlab examples used for kalman filter(fixed point version).
In this implementation of tracking a ball, we will track a live ball using Kalman filter.

The following Matlab project contains the source code and Matlab examples used for extended kalman filter(ekf) for gps.
This zip file contains a brief illustration of principles and algorithms of both the Extended Kalman Filtering (EKF) and the Global Position System (GPS).

The following Matlab project contains the source code and Matlab examples used for kalman equivalent lowpass filter.
A kalman filter based on a constant velocity model and constant process noise reaches is steady-state after few samples.