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`chaosys` gives the user the possibility to compute time series
data for a couple of dynamical systems, among which are Lorenz,
Chua, Roessler etc. This routine is not meant as a replacement for
Matlab's suite of functions for solving ODEs, but as a fast way to
generate some data sets to evaluate the processing capabilities
of TSTOOL. The integration is done by an ODE solver using an Adams Pece
scheme with local extrapolation
[151]. It is at least faster
than Matlab's native ODE solver. However, it is not possible to extend the set
of systems without recompiling `chaosys`.

**Syntax:**

`x = chaosys(length, stepwidth, initial_conditions, mode, parameters)`

**Input arguments:**

`length`- number of samples to generate`stepwidth`- integration step size`initial_conditions`- vector of initial conditions- mode:
- 0: Lorenz
- 1: Generalized Chua : Double Scroll
- 2: Generalized Chua : Five Scroll
- 3: Duffing
- 4: Roessler
- 5: Toda Oscillator
- 6: Van der Pol Oscillator
- 7: Pendulum

- parameters - vector of systems parameters. The order of the parameters is exactly the same as in the constructors of the DGL subclasses in the above file.

**Output arguments:**

`x`contains the output of the integration, organized as matrix of size samples by dim, where dim is the number of ODEs that define the system

**Example:**

x = chaosys(20000, 0.025, [0.1 -0.1 0.02], 0); plot(x(:,1));

The

**Lorenz:**-

**Generalized Chua:**-

**Duffing:**-

**Rössler:**-

**Toda oscillator:**-

**van der Pol oscillator:**-

**pendulum:**-

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