A system identification device for performing fast real-time identification for a system from input/output data includes a filter robust to disturbance, by setting the maximum energy gain from the disturbance to a filter error, as an evaluation criterion, smaller than a given upper limit. The filter estimates a state estimation value of a state of the system.

An apparatus for reducing belt slip of a vehicle, in which the vehicle includes an engine as a vibration source and an electric motor connected to the engine through a belt to transmit torque of the engine, includes: a signal generator configured to generate a reference signal with a frequency corresponding to vibration of the engine; an adaptive filter configured to calculate a filter coefficient to remove an error value between a rotational speed of the engine and a rotational speed of the electric motor and apply the filter coefficient to the reference signal to generate a reference torque signal; and a torque compensator configured to generate a belt slip compensation torque signal by changing an amplitude of the reference torque signal, and apply the belt slip compensation torque signal to determine a final torque command of the electric motor.

Example embodiments disclosed herein relate to filter coefficient updating in time domain filtering. A method of processing an audio signal is disclosed. The method includes obtaining a predetermined number of target gains for a first portion of the audio signal by analyzing the first portion of the audio signal. Each of the target gains is corresponding to a subband of the audio signal. The method also includes determining filter coefficients for time domain filtering the first portion of the audio signal so as to approximate a frequency response given by the target gains. The filter coefficients are determined by iteratively selecting at least one target gain from the target gains and updating the filter coefficient based on the selected at least one target gain. Corresponding system and computer program product for processing an audio signal are also disclosed.

A partitioned block frequency domain adaptive filter device includes a frequency domain adaptive filter configured for filtering a frequency domain representation of a time domain input signal depending on a set of filter coefficients consisting of a plurality of blocks of filter coefficients in order to produce a filtered signal; a plurality of parallel arranged filter update blocks; wherein each of the filter update blocks includes an adaptation module configured for executing an adaptation sequence including the steps of calculating an approximation of a constrained gradient update for the filter coefficients of the respective block of filter coefficients, and calculating a cumulative error introduced on the unconstrained gradient update; wherein each of the filter update blocks includes a correction module configured for executing a correction sequence including the steps of calculating a corrected constrained gradient update for the filter coefficients of the respective block of filter coefficients.

A signal-of-interest (SOI) may be separated from interference and/or noise using repeated reduced rank minimum mean-square error Fractional Fourier Transform (MMSE-FrFT) filtering and a low rank adaptive multistage Wiener filter (MWF). A number of stages in the MWF, L, may be chosen such that at the L.sup.th stage, the MSE between the SOI estimate and the true SOI is less than or equal to an error threshold (e.g., =0.001). By combining these filtering techniques, significant improvement in reducing the mean-square error (MSE) may be realized over single stage MMSE-FrFT, repeated MMSE-FrFT, and MMSE-FFT algorithmsindeed, by an order of magnitude or more.

Example embodiments disclosed herein relate to filter coefficient updating in time domain filtering. A method of processing an audio signal is disclosed. The method includes obtaining a predetermined number of target gains for a first portion of the audio signal by analyzing the first portion of the audio signal. Each of the target gains is corresponding to a linear subband of the audio signal. The method also includes determining a filter coefficients for time domain filtering the first portion of the audio signal so as to approximate a frequency response given by the target gains. The filter coefficients are determined by iteratively selecting at least one target gain from the target gains and updating the filter coefficient based on the selected at least one target gain. Corresponding system and computer program product for processing an audio signal are also disclosed.

The present disclosure provides a permanent-magnet fault-tolerant in-wheel motor based on an active sensorless strategy and drive and design methods thereof. The present disclosure proposes the permanent-magnet fault-tolerant in-wheel motor drive system based on an active sensorless strategy by considering sensorless operation performance in advance in a motor design stage. The present disclosure adopts fractional-slot concentrated windings, and ingeniously arranges alternating poles, a multi-layer magnetic barrier, and auxiliary permanent magnets, thus improving a sensorless operation accuracy of the motor while ensuring fault tolerance of the motor. The present disclosure proposes a frequency-band-adaptive secondary harmonic suppression strategy at a control layer to suppress an influence of a secondary salient harmonic on position observation and improve dynamic response performance of a system.

The present disclosure relates to adaptive filtering optimization methods based on a hyperbolic sine cost function. While the adaptive filtering optimization methods belong to the variable step-size class, however, the present disclosure describes a new approach requiring tuning of only one parameter. The present disclosure is further related to a family of higher order hyperbolic sine cost functions.

A signal-of-interest (SOI) may be separated from interference and/or noise using repeated reduced rank minimum mean-square error Fractional Fourier Transform (MMSE-FrFT) filtering and a low rank adaptive multistage Wiener filter (MWF). A number of stages in the MWF, L, may be chosen such that at the L.sup.th stage, the MSE between the SIM estimate and the true SW is less than or equal to an error threshold E (e.g., =0.001). By combining these filtering techniques, significant improvement in reducing the mean-square error (MSE) may be realized over single stage MMSE-FrFT, repeated MMSE-FrFT, and MMSE-FFT algorithms indeed, by an order of magnitude or more.

Various examples related to automatically composing universal filters are presented. In one example, among others, a system includes processing circuitry that can organize data received by the system into clusters or quasi-orthogonal regions, which are organized based upon a centroid threshold distance. The data can be organized by applying a cluster and retain operation, a cluster and merge operation or a split and retain operation. The system can then determine filter weights based at least in part upon centers of the clusters; update a content addressable filter bank (CAFB) based upon the filter weights; and filter subsequently received data based upon the CAFB. In another example, a method includes receiving and organizing initial data into clusters or quasi-orthogonal regions; determining filter weights based at least in part upon centers of the clusters; updating a CAFB based upon the filter weights; and receiving and filtering subsequent data based upon the CAFB.