Reconstruction deals with predicting the values of a quantity of interest at different locations other than those where sensors are located.įor example, one might predict the temperature at a point in the middle of a lake based on temperature readings taken at various other positions in the lake. Literature review along with examples and additional tips for The PySensors approach to reconstruction problems and Brunton et al. PySensors provides objects designed for the tasks of reconstruction andĬlassification. Some task nearly as well as if one had access to measurements at every Of sensor or measurement locations in a way that allows one to perform Sparse sensor placement concerns the problem of selecting a small subset
In addition to this, the utility may be used to configure FIFO mode and UVC parameters.Ī comprehensive Configuration Guide is available here: AN_435 – FT602 UVC Chip Configuration GuideĪdditionally, a video providing step-by-step instructions on how to use the FT602 Configuration Programmer application for customizing the chip configuration can be seen here.PySensors is a Scikit-learn style Python package for the sparse placement of sensors, either for reconstruction or classification tasks. The FT602 Configuration Programmer utility allows you to customize the FT602 device with different USB descriptors such as the Manufacturer String or Serial Number. In addition to this, the utility may be used to configure the mode of operation that the device will use such as clock speed, 245 FIFO or multi-channel (FT600) FIFO mode.Ī comprehensive user guide is available here: AN_370 FT60X Configuration Programmer User Guide The FT60x Chip Configuration Programmer utility allows FT600 and FT601 devices to be configured with different USB descriptors such as the Manufacturer String or Serial Number.
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