The following operations are supported on max-plus models
- Largest Eigenvalue – Determines the largest eigenvalue of the (first) matrix defined in the model;
- Eigenvectors – determines all (generalized) eigenvalues and eigenvectors of a square matrix defined in the model;
- Precedence Graph – convert a square matrix defined in the model to an precedence graph;
- Convert to Precedence Graph Image – convert a square matrix defined in the model to an precedence graph image;
- Convolution Analysis – Compute the convolution between two selected event sequences in the model. The names of the two event sequences in the model need to be provided as a comma-separated list;
- Convolution Transformation – Compute the convolution between two selected event sequences in the model – store the result as a new model;
- Delay Sequence – compute a delayed version of an event sequence where the sequence is delayed by a given number of samples; the name of the sequence and the number of samples to delay need to be provided;
- Scale Sequence – compute a scaled event sequence, where a given real-valued constant is added to all time stamps; the name of the event sequence and the constant to be added need to be provided;
- Maximum Analysis– Compute the maximum of the provided event sequences in the model; more than two event sequences may be provided;
- Maximum Transformation– Compute the maximum of selected event sequences in the model – store the result as a new model;
- Compute Output Vector Trace of State-Spaceย – compute the sequence of output vectors for a state-space model for given initial state and sequence of input vectors; the vectors contain the combined information from the vectors \(u(k)\), \(x(k+1)\) and \(y(k)\);
- Compute Output Vector Trace of State-Space Transform – compute the sequence of output vectors for a state-space model for given initial state and sequence of input vectors – store the result as a new model;
- Visualize Vector Trace – make a graphical vector trace for selected vector sequences and event sequences in the model.