Abstract: A classification system for classifying sensor samples in a sensor system, the sensor system comprising N force sensors each configured to output a sensor signal, where N?1, each sensor sample comprising N sample values from the N sensor signals, respectively, the classification system comprising: a classifier configured, for each of a series of candidate sensor samples, to perform a classification operation based on the N sample values concerned and generate a classification result which labels the candidate sensor sample as indicative of a defined target event, thereby generating a series of classification results corresponding to the series of candidate sensor samples, respectively; a determiner configured to output at least one event determination based on the series of classification results; and a controller configured to control the classifier and/or the determiner based on one or more controller input signals.

Abstract: A system for estimating parameters of an electromagnetic load may include an input for receiving an input excitation signal to the electromagnetic load, a broadband content estimator that identifies at least one portion of the input excitation signal having broadband content, and a parameter estimator that uses the at least one portion of the input excitation signal to estimate and output one or more parameters of the electromagnetic load.

Abstract: A non-transitory computer readable medium may have stored thereon data encoding a waveform signal for playback, wherein the waveform signal is generated by implementing a discrete time model of a physical electromagnetic load that emulates a virtual electromagnetic load and modifying a raw waveform signal to generate a waveform signal for driving the physical electromagnetic load by modifying the virtual electromagnetic load to have a desired characteristic and applying the discrete time model to the raw waveform signal to generate the waveform signal for driving the physical electromagnetic load.

Abstract: A method includes applying a high frequency signal to an electromechanical actuator and measuring a first response of the electromechanical actuator to the high frequency signal, estimating electrical parameters of the electromechanical actuator based on the first response, applying a low frequency broadband signal to the electromechanical actuator and measuring a second response of the electromechanical actuator to the low frequency broadband signal, and estimating mechanical parameters of the electromechanical actuator based on the second response and the estimated electrical parameters.

Abstract: The application describes techniques for adaptively setting a threshold that will be used to determine the gain applied to a haptics signal.

Abstract: A system may include an electromagnetic load capable of generating a haptic event and a haptic processor configured to receive at least one first parameter indicative of a desired perception of the haptic event to a user of a device comprising the electromagnetic load, receive at least one second parameter indicative of one or more characteristics of the device, and process the at least one first parameter and the at least one second parameter to generate a driving signal to the electromagnetic load in order to produce the desired perception to the user despite variances in the device that cause an actual perception of the haptic event to vary from the desired perception.

Abstract: A method for identifying a mechanical impedance of an electromagnetic load may include generating a waveform signal for driving an electromagnetic load and, during driving of the electromagnetic load by the waveform signal or a signal derived therefrom, receiving a current signal representative of a current associated with the electromagnetic load and a back electromotive force signal representative of a back electromotive force associated with the electromagnetic load. The method may also include implementing an adaptive filter to identify parameters of the mechanical impedance of the electromagnetic load, wherein an input of a coefficient control for adapting coefficients of the adaptive filter is a first signal derived from the back electromotive force signal and a target of the coefficient control for adapting coefficients of the adaptive filter is a second signal derived from the current signal.

Abstract: A multi-path audio amplification system that provides an output drive signal to electromechanical output transducers provides improved undistorted headroom, reduced path switching noise, and/or improved frequency response performance. Multiple signal amplification paths receive an audio input signal and have corresponding multiple output stages that have differing output impedances. A mode selector selects an active one of the multiple signal amplification paths is selected to supply the output drive signal. Outputs of the multiple output stages are coupled to the electromechanical transducer to provide the output drive signal and at least one of the multiple signal amplification paths includes an equalization filter for filtering the audio input signal to compensate for phase or gain differences referenced from the input to the outputs of the multiple output stages due to interaction between the differing output impedances and an impedance of the electromechanical transducer.

Abstract: A system for performing force sensing with an electromagnetic load may include a signal generator configured to generate a signal for driving an electromagnetic load and a processing subsystem configured to monitor at least one operating parameter of the electromagnetic load and determine a force applied to the electromagnetic load based on a variation of the at least one operating parameter.

Abstract: The application describes techniques for adaptively setting a threshold that will be used to determine the gain applied to a haptics signal.

Abstract: A method for identifying a mechanical impedance of an electromagnetic load may include generating a waveform signal for driving an electromagnetic load and, during driving of the electromagnetic load by the waveform signal or a signal derived therefrom, receiving a current signal representative of a current associated with the electromagnetic load and a back electromotive force signal representative of a back electromotive force associated with the electromagnetic load. The method may also include implementing an adaptive filter to identify parameters of the mechanical impedance of the electromagnetic load, wherein an input of a coefficient control for adapting coefficients of the adaptive filter is a first signal derived from the back electromotive force signal and a target of the coefficient control for adapting coefficients of the adaptive filter is a second signal derived from the current signal.

Abstract: The application describes techniques for adaptively setting a threshold that will be used to determine the gain applied to a haptics signal.

Abstract: A baseline unit for use in a sensor system, the sensor system comprising N force sensors which output N sensor signals, respectively, where N?1, the baseline unit configured to: monitor a measure of a rate of change of a sensor test signal, the sensor test signal being one of said N sensor signals or a signal derived from one or more of said N sensor signals; and in dependence upon the measure of the rate of change, control a stored baseline setting to control how a baseline test signal is calculated from said N sensor signals using a baseline-calculation method, the baseline-calculation method configured by the currently-stored baseline setting.

Abstract: A method for identifying a mechanical impedance of an electromagnetic load may include generating a waveform signal for driving an electromagnetic load and, during driving of the electromagnetic load by the waveform signal or a signal derived therefrom, receiving a current signal representative of a current associated with the electromagnetic load and a back electromotive force signal representative of a back electromotive force associated with the electromagnetic load. The method may also include implementing an adaptive filter to identify parameters of the mechanical impedance of the electromagnetic load, wherein an input of a coefficient control for adapting coefficients of the adaptive filter is a first signal derived from the back electromotive force signal and a target of the coefficient control for adapting coefficients of the adaptive filter is a second signal derived from the current signal.

Abstract: A multi-path audio amplification system that provides an output drive signal to electromechanical output transducers provides improved undistorted headroom, reduced path switching noise, and/or improved frequency response performance. Multiple signal amplification paths receive an audio input signal and have corresponding multiple output stages that have differing output impedances. A mode selector selects an active one of the multiple signal amplification paths is selected to supply the output drive signal. Outputs of the multiple output stages are coupled to the electromechanical transducer to provide the output drive signal and at least one of the multiple signal amplification paths includes an equalization filter for filtering the audio input signal to compensate for phase or gain differences referenced from the input to the outputs of the multiple output stages due to interaction between the differing output impedances and an impedance of the electromechanical transducer.

Abstract: A system may include an electromagnetic load capable of generating a haptic event and a haptic processor configured to receive at least one first parameter indicative of a desired perception of the haptic event to a user of a device comprising the electromagnetic load, receive at least one second parameter indicative of one or more characteristics of the device, and process the at least one first parameter and the at least one second parameter to generate a driving signal to the electromagnetic load in order to produce the desired perception to the user despite variances in the device that cause an actual perception of the haptic event to vary from the desired perception.

Abstract: A system may include an electromagnetic load capable of generating a haptic event and a haptic processor configured to receive at least one first parameter indicative of a desired perception of the haptic event to a user of a device comprising the electromagnetic load, receive at least one second parameter indicative of one or more characteristics of the device, and process the at least one first parameter and the at least one second parameter to generate a driving signal to the electromagnetic load in order to produce the desired perception to the user despite variances in the device that cause an actual perception of the haptic event to vary from the desired perception.

Abstract: A baseline unit for use in a sensor system, the sensor system comprising N force sensors which output N sensor signals, respectively, where N?1, the baseline unit configured to: monitor a measure of a rate of change of a sensor test signal, the sensor test signal being one of said N sensor signals or a signal derived from one or more of said N sensor signals; and in dependence upon the measure of the rate of change, control a stored baseline setting to control how a baseline test signal is calculated from said N sensor signals using a baseline-calculation method, the baseline-calculation method configured by the currently-stored baseline setting.

Abstract: A classification system for classifying sensor samples in a sensor system, the sensor system comprising N force sensors each configured to output a sensor signal, where N?1, each sensor sample comprising N sample values from the N sensor signals, respectively, the classification system comprising: a classifier configured, for each of a series of candidate sensor samples, to perform a classification operation based on the N sample values concerned and generate a classification result which labels the candidate sensor sample as indicative of a defined target event, thereby generating a series of classification results corresponding to the series of candidate sensor samples, respectively; a determiner configured to output at least one event determination based on the series of classification results; and a controller configured to control the classifier and/or the determiner based on one or more controller input signals.

Abstract: A classifier for classifying sensor samples in a sensor system, the sensor system comprising N force sensors each configured to output a sensor signal, where N>1, each sensor sample comprising N sample values from the N sensor signals, respectively, defining a sample vector in N-dimensional vector space, the classifier having access to a target definition corresponding to a target event, the target definition defining a bounded target region of X-dimensional vector space, where X?N, the classifier configured, for a candidate sensor sample, to perform a classification operation comprising: determining a candidate location in the X-dimensional vector space defined by a candidate vector corresponding to the candidate sensor sample, the candidate vector being the sample vector for the candidate sensor sample or a vector derived therefrom; and generating a classification result for the candidate sensor sample based on the candidate location, the classification result labelling the candidate sensor sample as ind