65 results about "Volterra series" patented technology

Non-linear interference cancellation techniques are provided for wireless transceivers. Non-linear reduction of interference of a transmit signal on a received signal in a transceiver device, comprises applying the transmit signal to a first non-linear system; applying the received signal to a second non-linear system; and subtracting an output of the first non-linear system output from an output of second non-linear system output to produce an interference mitigated received signal. The first non-linear system and/or the second non-linear system can be to implemented using one or more of a Volterra series and a Generalized Memory Polynomial Model. System parameters of the first non-linear system and/or the second non-linear system are adapted to reduce a power of the interference mitigated received signal.

A method is described for predistorting an input signal to compensate for non-linearities caused to the input signal in producing an output signal. The method comprises: providing an input for receiving a first input signal as a plurality of signal samples, x[n], to be transmitted over a non-linear element; providing at least one digital predistortion block comprising, a plurality of IQ predistorter cells coupled to the input, each comprising a lookup table (LUT) for generating an LUT output The at least one digital predistortion block block is configured to apply interpolation between LUT entries for the, plurality of LUTs; and generate an output signal, y[n], by each of the plurality of IQ predistorter cells by adaptively modifying the first input signal using interpolated LUT entries to compensate for distortion effects in the non-linear element. A combiner may be provided configured to combine the output signal samples, y_Q, from the plurality of IQ predistorter cells into a combined signal to generate the output signal, y[n], for transmission to the non-linear element. An error calculation block may be coupled to a digital predistortion adaptation block to determine and modify a predistortion performance.

A method and apparatus are used to predistort input signal samples according to Volterra Series Approximation Model using one or more digital predistortion blocks (300) having a plurality of predistorter cells (301-303), each including an input multiplication stage (366-367) for combining absolute sample values received from an absolute sample delay line (362) into a first stage output, a lookup table (368) connected to be addressed by the first stage output for generating an LUT output, and a plurality of output multiplication stages (371-372, 373-374) for combining the LUT output with samples received from the amplitude sample delay line (362) and signal sample delay line (363) to generate an output signal sample y_Q from said predistorter cell, where the output signal samples y_Q from the predistorter cells are combined at an output adder circuit (375) to generate one or more Volterra terms of a combined signal (y_OUT[n]).

The invention is a method for improved active sonar using a singular value decomposition filtering and a Volterra-Hermite Basis Expansion to model real active sonar measurements. The fitting model minimizes the sum of the squared errors between a measured channel response, z(t), and model response, y(t), which is a fitted Volterra Series solution. The model requires as input an excitation waveform, x(t), to which is fitted the model response, y(t). A contracted broadband cross-ambiguity function is used to correct the excitation waveform for Doppler and range effects. Once completed, the modeled response can be used to determine the linearity or non-linearity of the channel effects. Appropriate measures can be utilized to reduce these effects on the measured channel response.

A wireless communication device including two or more aggressor transmitters and a victim receiver that is adversely affected by intermodulation distortion (IMD) components associated with the signals transmitted by the two or more aggressor transmitters. Because the aggressor transmitters and the victim receiver are located on the same device, the transmit waveforms that contribute to the IMD components are known and available. More specifically, digital baseband samples used by the aggressor transmitters to generate the transmit waveforms are available. These digital baseband samples are used to reconstruct the IMD component on the wireless device. This reconstructed (estimated) IMD component is provided to the victim receiver, and is subtracted from a signal received by the victim receiver, thereby effectively removing the IMD component present in this received signal. An adaptive filter using a Volterra series can be used to estimate the IMD component in response to the transmitter digital baseband samples.

A sonar system and method are provided to extract and identify information about a particular target illuminated by an active sonar system. The present invention utilizes a Volterra Series Expansion in conjunction with a least squares procedure to estimate channel and target responses, which may be linear or nonlinear. The system estimates the channel and target responses for different orders of the Volterra Series Expansion and then selects the order for which a minimum error is determined with respect to a measured acoustic return signal. The system requires as inputs only the excitation waveform and the measured acoustic return signal.

The invention belongs to the field of digital communication distortion processing, in particular to an indirect learning predistortion linearized system based on Volterra series, comprising a predistortion signal generating module, a predistortion signal processing module, a feedback module and a parameter identification module. After the predistortion signal processing module processes a predistortion signal, an input signal of a radio-frequency power amplifier is obtained; after a small part of power in an output signal of the radio-frequency power amplifier is attenuated, the output signal enters the feedback module; after the feedback module processes a feedback signal, an input signal of the parameter identification module is obtained; the parameter identification module compares an output signal of same with the predistortion signal so as to obtain an error signal; and the error signal is gradually reduced and returned to zero by adjusting the parameters in the identification module and a predistorter. The invention has high stability and strong adaptive ability; the stability of the system does not need consideration, and meanwhile, the system can process multi-carrier signals; and the invention has good intermodulation distortion improvement effect and large adjustable range.

The present invention discloses an IGBT remaining useful life prediction method. By a phase space framing reconstruction technology, on the basis of reconstructing a phase space according to a differential entropy rate, the reconstructed phase space is subjected to Volterra-series input signal vector arrangement; correlation between input data and target output is considered, the optimal selection of each frame of input data is carried out, and the IGBT remaining useful life prediction method adopts a forward-backward algorithm and a least angle regression algorithm which are mature currently to use the optimal input data in input vectors as inputs of a model; a multiresponse sparse regression algorithm and a one-by-one extraction method are added on the basis of an original ELM model to cut off hidden layer nodes which are useless or have little effects, and three mixed neuronal activation functions are used, so that an established network has higher robustness and generalization. According to the present invention, difference of different inputs on a prediction model is sufficiently considered; the prediction model capable of dynamically updating each set of input data by an adaptive algorithm is designed; and prediction accuracy is greatly improved.

The invention discloses a power-amplifier digital pre-distortion device based on first-order truncation dynamic deviation reducing Volterra series of a nonlinear filter. The power-amplifier digital pre-distortion device is characterized in that a digital pre-distorter is used for performing digital pre-distortion treatment on an input digital baseband signal; a power amplifier is used for outputting an analogue baseband signal; the analogue baseband signal is coupled by power of an attenuation coupler, orthogonally demodulated by a broadband orthogonal demodulator and converted from analogue and digital by an analogue-to-digital converter to generate an output digital baseband signal; the input digital baseband signal and the output digital baseband signal are synchronized and then input in a pre-distorter training block; and the pre-distorter training block is used for performing parameter training by using a least squares algorithm to obtain model parameters. The invention also provides a power-amplifier digital pre-distortion method. According to the power-amplifier digital pre-distortion device and method, some other operations of high order operation and opening radical sign in the simplified Volterra series model are avoided; difficulty and complexity for processing digital signals are reduced; the model parameters are distributed more evenly; and nonlinear characteristics and memory effects of the power amplifier can be well compensated.

A radio transmission system comprising a plurality of Volterra Engine (VE) linearizers; a power amplifier (PA) coupled to the VE linearizers; a feedback circuitry coupled to the VE linearizers and the PA; and at least one adaptive controller coupled to the feedback circuitry, wherein each VE linearizer is coupled to at least another VE linearizer in series, in parallel, or both, and is configured to compensate for at least one distortion aspect of an output signal from the PA.

Provided in the invention is a detection method of a mechanical failure. The method comprises: continuation data at two terminals of an original signal are predicted according to a second-order Volterra series prediction model so as to obtain a non-boundary oscillation signal; redundant lifting wavelet packet decomposition is carried out on the non-boundary oscillation signal to eliminate frequency aliasing and generate a reconstruction signal; and singular value decomposition and noise reduction are carried out on the reconstruction signal and thus a fault feature signal is obtained, wherein the signal is used for mechanical failure detection.

Methods, systems and apparatus for modelling a power amplifier and pre-distorter fed by a multi-band signal are disclosed. According to one aspect, a method includes receiving a multi-band signal and generating a discrete base band equivalent, BBE, Volterra series based on the received multi-band signal, where the series has distortion products grouped according to determined shared kernels. The shared kernels are determined based on a transformation of a real-valued continuous-time pass band Volterra series without pruning of kernels.

The nonlinearity of power amplifiers (PAs) has been a severe constraint in performance of modern wireless transceivers. This problem is even more challenging for the fifth generation (5G) cellular system since 5G signals have extremely high peak to average power ratio. Nonlinear equalizers that exploit both deep neural networks (DNNs) and Volterra series models are provided to mitigate PA nonlinear distortions. The DNN equalizer architecture consists of multiple convolutional layers. The input features are designed according to the Volterra series model of nonlinear PAs. This enables the DNN equalizer to effectively mitigate nonlinear PA distortions while avoiding over-fitting under limited training data. The non-linear equalizers demonstrate superior performance over conventional nonlinear equalization approaches.

The invention discloses an internal damage detection method for an old mechanical part based on the Volterra series. The internal damage detection method comprises the steps of performing pulsed excitation on the old part to be detected through a pulse force hammer under the support of a free boundary; identifying a Volterra non-linear module of a system according to an input detection signal and a corresponding response signal, and giving out a non-linear output frequency response function estimation formula of the system; constructing a sensitive index function through a low-three-order non-linear output frequency response function, and estimating an actually detected value of the sensitive index function according to experiment test data; detecting the sensitivity of the sensitive index function to the internal damage of the old part through a series of tests, and reconstructing the sensitive index function to preferably select a suitable sensitive index function; evaluating an internal defect of the old part according to a non-linear characteristic sensitive index function value obtained through actually detected signal data, and constructing a classification standard for remanufacturing the cold part. The internal damage detection method is suitable for convenient, quick and accurate detection of a batch of old parts.

Improved techniques are provided for modeling a target Volterra series using an orthogonal parallel Weiner decomposition. A target Volterra Series is modeled by obtaining the target Volterra Series V comprised of a plurality of terms up to degree K; providing a parallel Wiener decomposition representing the target Volterra Series V, wherein the parallel Wiener decomposition is comprised of a plurality of linear filters in series with at least one corresponding static non-linear function, wherein an input signal is applied to the plurality of linear filters and wherein outputs of the non-linear functions are linearly combined to produce an output of the parallel Wiener decomposition; computing a matrix C. for a given degree up to the degree K, wherein a given row of the matrix C corresponds to one of the linear filters and is obtained by enumerating monomial cross-products of coefficients of the corresponding linear filter for the given degree; and determining filter coefficients for at least one of the plurality of linear filters, such that the rows of the matrix C are linearly independent.

The present invention discloses a transverse crack fault characteristic quantity extraction method of a rotor-bearing system. The method comprises the steps of: establishing a crack rotor-bearing system dynamics model to obtain a system dynamics equation and calculate system response signals in different crack angles; adding white noise simulation actual signals for system response in different crack angle, and performing EMD-CIIT noise reduction processing of the signals adding the white noise to obtain denoised signals; performing EMD decomposition of the denoised signals to extract IMF components; constructing a Volterra series model for each IMF component, and taking the Volterra model parameter of each IMF component as the horizontal vector of the matrix to construct a prediction parameter matrix; and taking the singular value of the obtained matrix as a system fault characteristic quantity. The transverse crack fault characteristic quantity extraction method can analyze the influence of different crack angles on the system response at the bearing position in different non-linear oil-film force.

The invention provides an adjustment method for matching of near-fault artificial seismic waves and a standard reaction spectrum. A calculation reaction spectrum is unfolded and decomposed into multiple layers, an optimized algorithm is used to carry out adjustment and wavelet reconstruction on coefficients which need adjusting, the standard reaction spectrum is matched rapidly in high efficiency,the calculation reaction spectrum matches the standard reaction spectrum more, and the Volterra level is zoomed in/out to improve the matching precision and calculation efficiency. Anti-seismic analysis can be carried out on an engineering structure, analysis on the anti-seismic design and structural power is more accurate and effective, a bridge design capability is optimized, a bridge safety coefficient is improved, the service life is prolonged, damage after seismic is reduced, maintenance cost after seismic is reduced, the matching difficulty is reduced greatly, guidance is provided for anti-seismic design of engineering building structures and the bridge structures, design of the engineering structure especially the bridge structure is optimized, and the design efficiency is improved.

A pertubative approach based on the Born approximation resolves weakly nonlinear circuit models without requiring explicit high-order device derivatives. Convergence properties and the relation to Volterra series are discussed. According to the disclosed methods, second and third order intermodulation products (IM2, IM3) and intercept points (IP2, IP3) can be calculated by second and third order Born approximations under weakly nonlinear conditions. A diagrammatic representation of nonlinear interactions is presented. Using this diagrammatic technique, both Volterra series and Born approximations can be constructed in a systematic way. The method is generalized to calculate other high-order nonlinear effects such as IMn (nth order intermodulation product) and IPn (nth order intermodulation intercept point). In general, the equations are developed in harmonic form and can be implemented in both time and frequency domains for analog and RF circuits.

The invention discloses a ground test unsteady aerodynamic loading method, and is used for solving the technical problem that an existing unsteady aerodynamic loading method has poor practicability. The technical scheme is to firstly process test structure measurement point data, a constant volume conversion method is adopted to achieve the reduction from a distributed unsteady aerodynamic force to an excitation concentrated force, an unsteady aerodynamic reduction model established based on computational fluid dynamics, and the unsteady aerodynamic reduction model based on Volterra series istransformed into a state space form. Due to the constant volume conversion method, the reduction from the distributed unsteady aerodynamic force to the excitation concentrated force is achieved, and the method is suitable for two-dimensional and three-dimensional complex surfaces. The unsteady aerodynamic reduction model based on computational fluid dynamics is established based on a Volterra series theory. The calculation accuracy is high, the ability to characterize a nonlinear system is strong, a minimum feature realization algorithm of the system is used for converting a reduced-order model into a state space form, and the method provides convenience for engineering application and has good practicability.