LTPDA Toolbox
Getting Started with the LTPDA Toolbox
What is the LTPDA Toolbox
System Requirements
Setting-up MATLAB
Additional 3rd-party software
Trouble-shooting
User Guide
Introducing LTPDA Objects
Types of User Objects
Creating LTPDA Objects
Working with LTPDA objects
Analysis Objects
Creating Analysis Objects
Saving Analysis Objects
Plotting Analysis Objects
Collection objects
Units in LTPDA
Parameter Lists
Creating lists of Parameters
Simulation/modelling
Built-in models of LTPDA
Generating model noise
Franklin noise-generator
Noise generation with given cross-spectral density
Parameteric models
Introduction to parametric models in LTPDA
Statespace models
Introduction to Statespace Models with LTPDA
Building Statespace models
Building from scratch
Building from built-in models
Modifying systems
Assembling systems
Simulations
Transfer Function Modelling
Pole/Zero representation
Building a model
Model helper GUI
Sum of partial fractions representation
Rational representation
Converting models between different representations
Converting models to digital filters
Signal Pre-processing in LTPDA
Downsampling data
Upsampling data
Resampling data
Interpolating data
Spikes reduction in data
Data gap filling
Noise whitening
Signal Processing in LTPDA
Digital Filtering
IIR Filters
FIR Filters
Filter banks
Applying digital filters to data
Discrete Derivative
Spectral Estimation
Introduction
Spectral Windows
What are LTPDA spectral windows?
Using spectral windows
Spectral Estimation Methods
Power spectral density estimates
Cross-spectral density estimates
Cross coherence estimates
Transfer function estimates
Log-scale power spectral density estimates
Log-scale cross-spectral density estimates
Log-scale cross coherence density estimates
Log-scale transfer function estimates
Fitting Algorithms
Polynomial Fitting
Markov Chain Monte Carlo
Markov Chain Monte Carlo - Simple experiment
Linear Parameter Estimation with Singular Value Decomposition
Linear least squares with singular value deconposition - single experiment
Linear least squares with singular value deconposition - multiple experiments
Iterative linear parameter estimation for multichannel systems - symbolic system model in frequency domain
Iterative linear parameter estimation for multichannel systems - ssm system model in time domain
Z-Domain Fit
S-Domain Fit
Graphical User Interfaces in LTPDA
The LTPDA Launch Bay
The LTPDA Workbench
Loading the LTPDA Workbench
Mouse and keyboard actions
The canvas
Building pipelines by hand
Block types
Adding blocks to the canvas
Setting block properties and parameters
Connecting blocks
Creating subsystems
Using the Workbench Shelf
Accessing the shelf
Creating shelf categories
Adding and using shelf subsystems
Importing and exporting shelf categories
Execution plans
Editing the plan
Linking pipelines
Executing pipelines
The LTPDA Workspace Browser
The pole/zero model helper
The Spectral Window GUI
The constructor helper
The LTPDA object explorer
Working with an LTPDA Repository
What is an LTPDA Repository
Connecting to an LTPDA Repository
Submitting LTPDA objects to a repository
Exploring an LTPDA Repository
Retrieving LTPDA objects from a repository
LTPDA Extension Modules
Class descriptions
ao Class
collection Class
filterbank Class
matrix Class
mfir Class
miir Class
parfrac Class
pest Class
plist Class
pzmodel Class
rational Class
smodel Class
ssm Class
timespan Class
Constructor Examples
General constructor examples
Constructor examples of the AO class
Constructor examples of the SMODEL class
Constructor examples of the MFIR class
Constructor examples of the MIIR class
Constructor examples of the PZMODEL class
Constructor examples of the PARFRAC class
Constructor examples of the RATIONAL class
Constructor examples of the TIMESPAN class
Constructor examples of the PLIST class
Constructor examples of the SPECWIN class
LTPDA Training Session 1
Topic 1 - The basics of LTPDA
Introducing Analysis Objects
Making AOs
Making a time-series AO
Basic math with AOs
Saving and loading AOs
Constructing AOs from data files
Writing LTPDA scripts
IFO/Temperature Example - Introduction
Topic 2 - Pre-processing of data
Downsampling a time-series AO
Upsampling a time-series AO
Resampling a time-series AO
Interpolation of a time-series AO
Remove trends from a time-series AO
Whitening noise
Select and find data from an AO
Split and join AOs
IFO/Temperature Example - Pre-processing
Topic 3 - Spectral Analysis
Power Spectral Density estimation
Example 1: Simply PSD
Example 2: Windowing data
Example 3: Log-scale PSD on MDC1 data
Empirical Transfer Function estimation
IFO/Temperature Example - Spectral Analysis
Topic 4 - Transfer function models and digital filtering
Create transfer function models in s domain
Pole zero model representation
Partial fraction representation
Rational representation
Transforming models between representations
Modelling a system
How to filter data
By discretizing transfer function models
By defining filter properties
IFO/Temperature Example - Simulation
Topic 5 - Model fitting
System identification in z-domain
Generation of noise with given PSD
Fitting time series with polynomials
Non-linear least squares fitting of time series
IFO/Temperature Example - signal subtraction
LTPDA Training Session 2
Topic 1 - LTPDA Review.
Introducing objects in LTPDA
Saving and loading objects
Review of spectral estimators
Preparing data segments (splitting)
Review of filtering and whitening in LTPDA
LTPDA scripting best practices
Introduction to LTPDA extension modules
Topic 2 - Simulating LPF noise in LTPDA.
Introduction to state-space models in LTPDA
Introduction to the LPF state-space models in LTPDA
Building an LTP model
Introduction to the various LPF noise models
Building an LPF model
Simulating noise
Simulating harmonic oscillator noise
Simulating capacitive actuation noise
Simulating LPF noise
Changing system parameters
Simulate LPF with matched stiffness
Topic 3 - Estimation of equivalent acceleration.
Principles and theory
Tools for estimating the equivalent acceleration in LTPDA
Estimate equivalent acceleration from simulation data
Topic 4 - Simulating LPF with injected signals.
LPF model inputs
Building signals
How to inject signals
Simulate LTP with injected signals (no noise)
Inject noise signals to LTP
Estimate tranfser functions from simulated signals, compare with Bode estimates
Simulate LPF with injected signals
Topic 5 - Introduction to system identification of LPF.
Introduction to LTPDA's parameter estimation tools
A simplified LPF system identification experiment
Create simulated experiment data sets
Build state-space LTP models for system identification
Calculate expected covariance of the parameters (FIM)
Perform system identification to estimate desired parameters
Parameter estimation with MCMC
Linear Parameter Estimation with Singular Value Decomposition
Building whitening filters
Linear Parameter Estimation
Results and Comparison
Use parameter estimates to estimate residual differential acceleration
Examples
Demos
Release Notes
Version 2.8 LTPDA Toolbox Software
Version 2.7.1 LTPDA Toolbox Software
Version 2.7 LTPDA Toolbox Software
Version 2.6.1 LTPDA Toolbox Software
Version 2.6 LTPDA Toolbox Software
Version 2.5.5 LTPDA Toolbox Software
Version 2.5.4 LTPDA Toolbox Software
Version 2.5.3 LTPDA Toolbox Software
Version 2.5.2 LTPDA Toolbox Software
Version 2.5.1 LTPDA Toolbox Software
Version 2.5 LTPDA Toolbox Software
Version 2.4 LTPDA Toolbox Software
Version 2.3.1 LTPDA Toolbox Software
Version 2.3 LTPDA Toolbox Software
Version 2.2 LTPDA Toolbox Software
Version 2.1 LTPDA Toolbox Software
Version 2.0.1 LTPDA Toolbox Software
Version 2.0 LTPDA Toolbox Software
LTPDA Web Site
