Nonlinear Analysis in Real Time

The NLyzer

13th June 2010

The NLyzer software enables you to analyze your data with new methods based on the concept of Nonlinear Dynamical and Complex Systems as well as with information theoretical measures and linear methods.

Its graphical editor allows you to combine any method and use it sequentially or in parallel with others. This enables immediate comparison and visualization of results. It is also especially suited for large and multidimensional data streams.
It features a template library with predefined ready-to-run data analysis setups.
Fast algorithms allow you to sweep through your data in real time. Each algorithm is encapsuled in its own process to optimally accomplish fast execution on single, multi-core or multi-processor PC’s.

Algorithms include

  • nonlinear prediction
  • nonlinear parameter estimation
  • analysis using information theory
  • dependance analysis within several nonlinearly coupled data streams
  • conditional entropy
  • fractal dimension
  • FFT, correlation, filtering …

Input and output of data includes

  • file I/O
  • audio support
  • Excel


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Todays Feature: Dependance Analysis

1st June 2010

- Verify functional (in)dependance between data sets with information theoretic / nonlinear methods.

This template calculates the dependance between data sets. The linear dependance is calculated via the cross correlation. Also the conditional entropy (relative to a deterministic dependance) between channels is shown to discriminate further (in)dependances.

Use it to:

  • find a dependance between data sets
  • verify independance between data sets
  • failure analysis and tracking
  • verify information flow and its direction between data sets
  • determine which data set can be described by another
  • monitor online changes of dependance online
  • show difference in linear / nonlinear (functional) dependance

more …

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Featured Template: Nonlinear Modelling

21st May 2007

- Find an optimal polynomial model to describe a dependance on 3 independant variables.

This template is an example of finding a polynomial model f(x,y,z) for a data set. In other words: Given 4 sets of data values, can one be described as a function of the 3 others? This template is easily extended to analyze a function of any number of data sets, and it also covers the simple nonlinear function f(x), too.

Use it to:

  • calculate the equations to describe a nonlinear functional dependance between 2 or more data sets
  • find a dependance between data sets
  • verify independance between data sets
  • verify deviations of new data model from a model calculated from prior aquired or test data
  • verify system changes by online monitoring of prediction error
  • verify deviations online from stored or edited model

more …

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