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.

A filtering device includes a low-pass filter (LPF), a noise estimation circuit and a first combining circuit. The LPF receives and filters a pre-filtering signal to generate an output signal of the filtering device. The noise estimation circuit estimates an estimated noise signal according to the output signal and the pre-filtering signal. The first combining circuit subtracts the estimated noise signal from an input signal of the filtering device to generate the pre-filtering signal.

A filtering device includes a low-pass filter (LPF), a noise estimation circuit and a first combining circuit. The LPF receives and filters a pre-filtering signal to generate an output signal of the filtering device. The noise estimation circuit estimates an estimated noise signal according to the output signal and the pre-filtering signal. The first combining circuit subtracts the estimated noise signal from an input signal of the filtering device to generate the pre-filtering signal.

One example includes an equalizer system. The system includes a filter system configured to receive digital sample blocks associated with an input signal and to provide equalized digital sample blocks associated with the respective digital sample blocks based on adaptive tap weights. Each of the digital sample blocks includes samples and each of the equalized digital sample blocks includes equalized samples. The system also includes a sample set selector to select a subset of equalized samples from each of the equalized digital sample blocks at the output of the filter and an error estimator configured to implement an error estimation algorithm on the subset of the equalized samples to determine a residual error associated with the equalized samples. The system further includes a tap weight generator configured to generate the adaptive tap weights in response to the residual error and to provide the adaptive tap weights to the filter.

This disclosure describes systems, methods, and apparatus for a digital-to-analog (DAC) converter, that can be part of a variable capacitor and/or a match network. The DAC can include a digital input, an analog output, N contributors (e.g., switched capacitors), and an interconnect topology connecting the N contributors, generating a sum of their contributions (e.g., sum of capacitances), and providing the sum to the analog output. The N contributors can form a sub-binary sequence when their contributions to the sum are ordered by average contribution. Also, the gap size between a maximum contribution of one contributor, and a minimum contribution of a subsequent contributor, is less than D, where D is less than or equal to two time a maximum contribution of the first or smallest of the N contributors.

A motor control apparatus includes: an oscillation instruction unit outputting an oscillation instruction signal; a filter unit performing filtering processing having frequency characteristic defined by a filter parameter; an oscillation forcing unit configuring a control loop in an oscillation period together with the filter unit, a current control unit, a motor, and a velocity calculation unit and causing the control loop to oscillate during the oscillation period in which the oscillation instruction signal is in the on-state; an amplitude evaluation unit acquiring, as an evaluation value, the amplitude ratio of an input signal to an output signal of the oscillation forcing unit when the control loop oscillates; and a filter adjustment unit comparing evaluation values provided when filter parameter candidates are set in the filter unit sequentially, selecting one of the filter parameters achieving a smaller evaluation value, and setting the selected filter parameter in the filter unit.

New measurement inputs for Kalman Filter or similar estimation approaches (at each sample) may include: DSRC messages from roadside transmitters (RSTs), such as: how long it takes for a DSRC signal from one or more fixed RSTs to reach the vehicle and comparison of that information with vehicle position estimates from a signal propagation model, which is based on how long it takes a DSRC signal to reach the vehicle GPS location from a fixed known RST location. From such measurements, it can be determined how much longer (or shorter) it takes to receive the RST message compared to the previous sample, which, in turn, gives an idea how far the vehicle has moved over a sample relative to a fixed RST location.

A modulator includes an analog integrator including an analog circuit and a quantizer quantizing its output signal. An external input signal is input thereto. A modulator is coupled to the latter stage of the modulator, and includes a quantizer. A probe signal generation circuit injects a probe signal to the modulator. An adaptive filter searches for a transfer function of the modulator by observing an output signal of the quantizer in accordance with a probe signal. Another adaptive filter searches for a transfer function of the modulator by observing an output signal of the quantizer in accordance with the probe signal. A noise cancel circuit cancels a quantization error generated by the quantizer using search results of the adaptive filters.

Systems, methods, and devices are provided for compensating for distortion of a contactless communication channel. The electronic device may include a radio frequency system that itself includes antenna to transmit and receive data using near-field communication (NFC) and an NFC signal processing circuitry. The NFC signal processing circuitry may receive an NFC signal via a communication channel formed between the electronic device and another electronic device and may determine a baseband reference waveform associated with the electromagnetic NFC signal and may determine an error between a portion of the electromagnetic NFC signal and the baseband reference waveform. Furthermore, the NFC signal processing circuitry may determine whether the error is outside of an acceptable error threshold range and, in response to the error being outside of the acceptable error threshold range, train a filter response of the NFC signal processing circuitry to estimate the communication channel.

Highly efficient digital domain sub-band based receivers and transmitters.