Dialog Semiconductor B.v.

Renesas Design Netherlands B.v.

Greenpeak Technologies B.v.

Wessel Harm Lubberhuizen

Ashley Hughes

Paul Shields

Fotios Kontomichos

Marinus Wilhelmus Kruiskamp

Hans Van Driest

Michiel Andre Helsloot

Johannes Steensma

Jakobus Johannes Verhallen

Georgios Flamis

Niels Schutten

A computer-implemented method of automated filter design comprising designing a feedback filter for an active noise cancelling system.

Tools and methods for designing filters for use in active noise cancelling systems

A computer-implemented method for automatically designing a feedforward filter that is optimized for an audio transparency mode of operation of an audio device, the audio device comprising the feedforward filter and a feedback filter, the method comprising optimizing the feedforward filter for the audio transparency mode of operation, wherein optimization of the feedforward filter is dependent on the feedback filter.

Method for automatically designing a feedforward filter

An active noise cancellation (ANC) system is presented. The ANC system includes a transducer; a first microphone; and a first adaptive filter coupled to a calculator. The calculator generates an error signal based on a difference between a filtered input signal and a signal from the first microphone. The filtered input signal is based on a first transfer function estimate of the transducer-to-first microphone transfer function via a first acoustic path. The calculator updates coefficients of the first adaptive filter using the error signal and generates with the first adaptive filter a first noise-cancellation signal.

Active noise cancellation system

A method of automated feedforward filter design comprising designing a feedforward filter for a system implementing active noise cancelling is described. The method includes designing the feedforward filter by determining a filter transfer function of the feedforward filter. The filter transfer function is determined using a least square method. The method also includes determining the filter transfer function by defining a target transfer function of the feedforward filter and applying the least square method using the target transfer function to determine a filter expression for the filter transfer function. The least square method is a weighted least square method.

Tools and methods for designing feedforward filters for use in active noise cancelling systems

A key word detection apparatus and a method for low-power voice-activated devices are presented. A first signal processing module operates with a first transducer to receive an incoming signal and generates a first sample. A second signal processing module operates with a second transducer which receives an incoming signal and generates a second sample. In summary, a signal processing system, in particular a key word detection system, has a first low power module that wakes up a second higher power module. The second module uses signals from the first module in order to improve accuracy of key word detection or other signal processing tasks.

Signal processing

A digital signal processing system for multiplying a digital value and a digital signal. The digital signal processing system receives the digital value in an encoded format, and multiplies the digital value with the digital signal. The digital value in the encoded format has an offset, which is encoded as a floating point. The disclosure provides a digital processing system that can carry out a multiplication operation with a smaller area, less complexity and/or reduced power usage compared with known multipliers.

Digital signal processing system

A digital filter for filtering a pulse density modulation (PDM) signal is presented. The filter has a first filter circuit to receive an input signal and to provide a filtered input signal at successive time steps which include a first filtered value at the first time step and a second filtered value at a second time step. The filter also has a quantizer to provide an output signal comprising output values at successive time steps and a filter variable circuit with a first multiplication circuit to receive the first filter variable, and divide the first filter variable by a first gain factor and a first summing circuit configured to receive the divided first filter variable, receive the output signal, and add the divided first filter variable and the first output value and a second multiplication circuit and a delay circuit.

Digital filter

A computer-implemented method for automatically optimizing a hybrid active noise cancellation system, the hybrid active noise cancellation system comprising a feedback filter and a feedforward filter, the method comprising optimizing the feedforward filter, thereby optimizing the hybrid active noise cancellation system, wherein optimization of the feedforward filter is dependent on the feedback filter.

Optimization of a hybrid active noise cancellation system

A method of automated feedforward filter design comprising designing a feedforward filter for a system implementing active noise cancelling is described. The method includes designing the feedforward filter by determining a filter transfer function of the feedforward filter. Optionally, the filter transfer function is determined using a least square method. The method also includes determining the filter transfer function by defining a target transfer function of the feedforward filter and applying the least square method using the target transfer function to determine a filter expression for the filter transfer function. Optionally, the least square method is a weighted least square method.

A digital filter structure and related method of digital filtering are presented. The digital filter structure is arranged to receive one or more clocked input signals having a first clock rate, and which is driven at a second clock rate higher than said first clock rate. The digital filter structure has a plurality of delay elements and multiplexing circuitry arranged to selectively engage the delay elements such that, at every clock cycle of the digital filter structure, a filter operation is performed on a different stream of data. The disclosure can be applied in many different contexts. One particular implementation example is that of an adaptive noise cancellation (ANC) system using sigma-delta infinite impulse response filters. In this context the present disclosure minimizes latency and hardware implementation area by requiring only one filtering circuit for multiple channels of data to be filtered.

Digital filter structure

Methods, structures and computer program products for digital sample rate conversion are presented. An input digital sample with a first frequency is converted to an output sample with a second frequency. A sample rate conversion circuit is provided which provides an enhanced transposed farrow structure that enables an optimised trade-off between noise levels and computational complexity. Each output sample is derived by convolution of a continuous time interpolation kernel with a continuous time step function representing the input sample stream. In a sample rate conversion structure, there is a trade-off between the quality and the computational complexity. The quality is defined as a ratio between the (wanted) signal power and the (unwanted) noise power. The computational complexity may be defined as the average number of arithmetic operations that are required to generate one output sample. A higher computational complexity will generally lead to a higher power consumption and larger footprint.

Digital sample rate conversion

An anti-noise signal generator and a method of generating an anti-noise signal are presented. The anti-noise generator includes a first microphone input to receive a first sigma-delta modulated signal at a microphone sampling frequency. The first microphone input is coupled to a combiner via a first path and a second path. The combiner is adapted to combine a first filtered signal from the first path and a second filtered signal from the second path to generate the anti-noise signal. The first path includes a first digital filter adapted to operate at a filter frequency equal or greater than the microphone sampling frequency. The second path includes a second digital filter. The first digital filter may be a sigma-delta based filter that includes a sigma-delta modulator.

Anti-noise signal generator

Methods and devices for distance measuring/ranging, as well as location measurements both in 2D and 3D are presented. More specifically, the methods and devices are for determining the time of arrival of a radio frequency signal. A method of determining a time of arrival of a radio frequency signal in a receiving device as received from a transmitting device includes receiving a radio frequency signal, determining a first phase. The first phase is defined as a phase of the received radio frequency signal. The method also includes obtaining a second phase. The second phase is defined as a phase of a reference radio frequency signal. The method also includes determining the time of arrival of the radio frequency signal based on comparing the first and second phases.

Apparatus and method of flight measurement

A signal processing structure and method are presented. A first digital filter operates on received sigma-delta modulated (SDM) input signals. A second pre-processing digital filter receives a SDM input signal, directly low pass filter the SDM input signal and provides an output SDM signal. The output sigma-delta modulated signal is provided as an input for said first digital filter. In standard digital systems operating with digital microphones, filtering of the microphones' output signal requires to first convert the signal into pulse code modulation (PCM), then filter and finally convert back to pulse density modulation (PDM). This approach increases the latency of the system because decimation and interpolation must be performed in order to pass from PDM to PCM. By using filters that operate directly on the oversampled PDM output of the digital microphones it is possible to reduce the latency of the system and minimize the hardware area.

Signal processing structure

A method of data calibration, and in particular sensor calibration, which involves gathering an initial first estimate and then binning the data samples, so that calibration can be performed without the need for a known reference stimulus. The present disclosure relates to calibration of vectors in a measurement system, and in particular to calibration of a correction function for systematic errors in successive data vectors. There is provided a method of determining a vector calibration function comprising: binning successive data vectors; and optimising the binned data vectors once data vectors allocated to a minimum number of unique bins have been observed. The method comprises establishing an initial calibration estimate and where the binning and optimising are performed based on said initial calibration estimate.

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Delden, Netherlands

Wessel Harm Lubberhuizen