What's New in ASCMO-STATIC & ASCMO-DYNAMIC V5.16

MLP and MLP Classification models can now be exported to Embedded AI Coder for generating optimized C code.

Overview: Exports Supported by Model Type

Model Export to Embedded AI Coder

Export to Embedded AI Coder
Added a new menu option File > Generate Code with Embedded AI Coder. This allows you to directly generate C code from ASCMO using the Embedded AI Coder.

File Menu (ASCMO-STATIC)
Automated Machine Learning now includes an option to restrict the search to model types supported by Embedded AI Coder.

Parameter Range Automated Machine Learning (ASCMO-STATIC)
The View > Show Marked Data option now shows the absolute values of the data points rather than the adjusted ones.
Introduced a new Visualization view to better explore and manage your data. It allows you to create views like in MOCA with tables, scatter plots, histograms, measured vs. predicted, and contour plots.

Data Menu (ASCMO-STATIC)

Visualization

Models can now be exported to the Embedded AI Coder to generate efficient C code. Note: All RNN andCNN model settings are now supported by export to Embedded AI Coder apart from “Learn Initial States”.

Model Export to Embedded AI Coder

Export to Embedded AI Coder
Automated Machine Learning now includes an option to restrict the search to model types supported by Embedded AI Coder.

Parameter Range Automated Machine Learning (ASCMO-DYNAMIC)
Added a new menu option File > Generate Code with Embedded AI Coder. This allows you to directly generate C code from ASCMO using the Embedded AI Coder.

File Menu (ASCMO-DYNAMIC)
Added integration between Automated Machine Learning and the Embedded AI Coder to report and constrain model resource usage (RAM, ROM, and inference time).

Parameter Range Automated Machine Learning (ASCMO-DYNAMIC)
CNN models can now be exported to FMU and Simulink.

Overview: Exports Supported by Model Type