The present invention is a computationally-efficient compensator for removing nonlinear distortion. The compensator operates in a digital post-compensation configuration for linearization of devices or systems such as analog-to-digital converters and RF receiver electronics. The compensator also operates in a digital pre-compensation configuration for linearization of devices or systems such as digital-to-analog converters, RF power amplifiers, and RF transmitter electronics. The multi-dimensional compensator effectively removes linear and nonlinear distortion in these systems by accurately modeling the state of the device by tracking multiple functions of the input, including but not limited to present signal value, delay function, derivative function (including higher order derivatives), integral function (including higher order integrals), signal statistics (mean, median, standard deviation, variance), covariance function, power calculation function (RMS or peak), or polynomial functions. The multi-dimensional compensator can be adaptively calibrated using simple arithmetic operations that can be completed with low processing requirements and quickly to track parameters that rapidly change over time, temperature, power level such as in frequency-hopping systems.

Techniques are provided for diminishing latency in a DAS fronthaul network configured to convey time-domain transport data, e.g., time-domain digital transport data or time-domain digital data. Other techniques are provided for obtaining higher DAS fronthaul efficiency.

A method and a device for updating a coefficient vector of a finite impulse response filter are provided. The update method includes: obtaining an updated step-size diagonal matrix for a coefficient vector of the FIR filter; and obtaining an updated coefficient vector of the FIR filter based on the updated step-size diagonal matrix.

The present invention is directed to energy-efficient hibernation in indoor wireless localization systems. A tag passively associates with a detection point (DP) and establishes a reveille time. The tag will awaken at the reveille time and send or receive a beacon to or from its associated DP. If the tag is receiving a beacon, it will awaken, receive, phase-lock its clock based on when the beacon was expected and when it was actually received, and return to hibernation. The DP transmits a scattershot of beacons, one for every tag in the system. If the tag is sending a beacon, it will awaken, send its beacon, and return to hibernation. The DP will receive the beacon and adjust its own clock based on the delay between when the beacon was expected and when it was actually received. The tag will broadcast its location to the DP on a set interval.

A power management system may include an energy source and a generator driven by a gas turbine engine to output generator power to a common bus. A source power converter is electrically coupled between the energy source and the common bus. A controller circuitry includes an adaptive filter to filter a power signal indicative of power consumption of a variable load on the common bus, and outputs a filtered signal as a load demand signal to the generator. A source demand error signal is also output to control the source power converter to supply power from the energy source to the common bus. The controller circuitry is further configured to automatically adjust the adaptive low pass filter in accordance with the power consumption of the dynamic load and the load demand signal of the generator.

The invention relates to a method for filtering an input signal (3b, 4b, 5b) relative to a physical variable of a turbine engine (9), the input signal being digitised, the method implementing frequency filtering of said signal in a computer (6) of a control system (7) of said turbine engine (9), said signal being provided at the input of the computer, a digital derivative of said signal being intended for being used by the control system (7), characterised in that it involves: detecting an amplitude variation of said variable on said input signal, by a step of generating a second derivative signal (S) of the input signal and a step of comparing a value of the second derivative value of the input signal with at least one predetermined threshold (S.sub.1 . . . S.sub.n); and adapting the frequency filtering of said input signal as a function of the detected amplitude variation of said variable, by a step of controlling a controlled filter (PB.sub.11) capable of applying frequency filtering to the input signal, so that the controlled filter applies or does not apply the frequency filtering as a function of a result of the comparison step.

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.

A noise reduction system includes sensors configured to generate an input signal, an adaptive filter configured to represent a transfer function of a path traversed by the input signal, one or more processing devices, and one or more transducers. The processing devices receive the input signal and generate an updated set of filter coefficients of the adaptive filter by separating the input signal into frequency subbands; determining for each subband, coefficients of a corresponding subband adaptive module; and combining the coefficients of multiple subband adaptive modules. Determining the coefficients of the corresponding subband adaptive module includes selecting a subset of a precomputed set of filter coefficients of the adaptive filter. The processing devices process a portion of the input signal using the updated set of filter coefficients of the adaptive filter to generate an output that destructively interferes with another signal traversing the path represented by the transfer function.

A method for adaptive signal processing is provided. In the method, a second vector is obtained by initializing a first vector without regularization of a cost function. The cost function is regularized with the first vector and the second vector as variables. The first vector is updated based on an input signal, according to the regularized cost function. Then, an output signal is provided based on the updated first vector. The second vector is updated based on the update of the first vector. An apparatus for adaptive signal processing is provided accordingly. The method and the apparatus are well compatible with existing adaptive signal processing. The convergence coefficients of the adaptive filter system become more stable. Moreover, impact of an extra penalty added to the cost function on a bias can be minimized, and the increased complexity of the system is very limited.

According to one embodiment, a sensor module includes at least one sensor and at least one switch. The sensor includes a first piezoelectric element. The first piezoelectric element includes a first electrode. The first piezoelectric element is set with a resonance frequency to resonate at a vibration frequency of a detection target. The switch includes a second piezoelectric element. The second piezoelectric element includes a second electrode connected to the first electrode and a third electrode electrically separated from the second electrode.