A signal processing circuit includes a correction function determination section for performing correction function determination processing, and a correction processing section for performing correction processing. The correction processing is to correct first and second detection signals by using a correction function to thereby generate first and second corrected signals. The correction function is expressed as a coefficient matrix for converting a first column vector containing the first and second detection signals as elements into a second column vector containing the first and second corrected signals as elements. The correction function determination processing includes performing arithmetic processing using a plurality of pairs of values of the first and second detection signals to determine one or two provisional correction coefficients as the correction coefficients of the correction function.

This disclosure is directed to methods, computer program products, and systems for calibrating one or more remote sensing devices in an environment. The disclosed technology relates to a calibration device configured to determine measurement data within an environment. The calibration device may transmit the measurement values, or other calibration data items, to a remote sensing device via a wireless link while the remote sensing device stays with a structure in which the remote sensing device is commissioned to operate. In response to receiving the calibration data items, the remote sensing device may adjust one or more settings of the remote sensing device in order to satisfy a calibration threshold.

The present invention includes a body case having a biological sample sensor mounting portion on one end side, a temperature sensor (A) provided on the one end side inside the body case, a measurement portion connected to the biological sample sensor mounting portion, and a control portion connected to the measurement portion. A temperature sensor (B) is provided on one other end side inside the body case, and when measurement is performed by the measurement portion, temperature change amounts in the two end portions are compared using the temperature sensors (A) and (B). Furthermore, a measurement value obtained by the measurement portion is corrected using temperature information from either one of the temperature sensors (A) or (B) that is provided in the end portion on the side where the temperature change is smaller.

The disclosure relates to a method for calibrating a sensor component with a calibration model, said method comprising: applying an acting physical variable and at least one disturbance variable to the sensor component; and acquiring training data sets at a plurality of evaluation times, wherein a training data set at each evaluation time is acquired by: providing a value for the physical variable acting on the sensor component and a corresponding desired sensor variable, which is intended to represent the value of the physical variable acting on the component; acquiring an electrical measured variable representing the physical variable; acquiring the at least one disturbance variable; and training the calibration model with the training data sets so that said model maps the at least one disturbance variable to calibration parameters, wherein a difference between the desired sensor variable and the sensor variable is used as a loss function.

In an embodiment, an apparatus is disclosed that comprises a plurality of resistors arranged as a reverse bridge and configured to convert an input voltage to a scaled output voltage. The scaled output voltage is scaled to a target format based at least in part on a range of the input voltage and a fixed value of the plurality of resistors. The input voltage is generated based at least in part on at least one signal generated by a sensor based at least in part on a measurement of a property of a measurement target. At least one of the plurality of resistors has a resistance value of R and at least another of the plurality of resistors has a resistance value of R plus or minus ΔR.

A vehicle includes an electric machine having a number of pole pairs, N, a position sensor having a number of pole pairs, M, that generates output indicative of a rotational position of the electric machine, and one or more controllers. The one or more controllers generate a remapped rotational position according to a product of the rotational position and L/N, generate a scaled position according to a product of the remapped rotational position and N/M, and command the electric machine to produce a specified torque or speed based on the scaled position. M is not equal to and not a factor of N, and L is a minimum common multiplier of N and M.

In an embodiment, an apparatus is disclosed that includes a plurality of resistors arranged as a reverse bridge and configured to convert an input voltage to a scaled output voltage. The scaled output voltage is scaled to a target format based at least in part on a range of the input voltage and a fixed value of the plurality of resistors. The input voltage is generated based at least in part on at least one signal generated by a sensor based at least in part on a measurement of a property of a measurement target.

A sensor interface circuit comprises an input arranged to receive a sensor signal being an electrical signal representative of an electrical quantity. The electrical quantity includes a physical quantity converted in a sensor. The sensor interface circuit includes conversion means arranged for converting the sensor signal into a digital signal, memory to store sensor characterisation data, signal processing means adapted to obtain a first sensor result by processing the digital signal using the sensor characterisation data, and an output unit arranged to receive and output the first sensor result, the digital signal and the sensor characterisation data.

Embodiments of the present invention are directed to a noise-model based sensor converter configured to map a sensor measurement output to discrete, nonlinear steps of constant uncertainty. In a non-limiting embodiment of the invention, the sensor converter receives an output signal from a sensor. The output signal can include a measurement. The sensor converter can also receive a noise model. The output signal is mapped to a discrete set of steps based on the noise model. The discrete set of steps are nonlinearly spaced to provide constant uncertainty between adjacent steps. The sensor converter generates an output based on the discrete set of steps.

A measurement device with automatic optimization capabilities comprises at least one signal processing component with a physical detector and a virtual detector component comprising at least one virtual detector for a signal processing component without physical detector. The physical detector is configured to physically measure a measurement value assigned to the signal processing component. The virtual detector component is configured to use a model of a signal processing chain from the physical detector to the location of the virtual detector. The model comprises at least one model parameter for the signal processing chain. The measurement device is configured to adapt the virtual detector component with respect to a measurement type for the signal to be measured. The virtual detector component is configured to use the model and the at least one measurement value. The virtual detector component is configured to determine a virtually determined value based on the model and the at least one measurement value. The measurement device is configured to use the virtually determined value to determine a setting for the measurement device. In addition, a method of setting a measurement device is described.