1698 results about "Time frequency domain" patented technology

A method embodiment includes implementing, by a base station (BS), a grant-free uplink transmission scheme. The grant-free uplink transmission scheme defines a first contention transmission unit (CTU) access region in a time-frequency domain, defines a plurality of CTUs, defines a default CTU mapping scheme by mapping at least some of the plurality of CTUs to the first CTU access region, and defines a default user equipment (UE) mapping scheme by defining rules for mapping a plurality of UEs to the plurality of CTUs.

An audio fingerprint is generated by transforming an audio sample of a recording to a time-frequency domain and storing each time-frequency pair in a matrix array, detecting a plurality of local maxima for a predetermined number of time slices, selecting a predetermined number of largest-magnitude maxima from the plurality of local maxima detected by said detecting, and generating one or more hash values corresponding to the predetermined number of largest-magnitude maxima.

The invention relates to a seamless switching method for voice / music dual-mode en-decoding. When a dual-mode en-decoder switches from CELP voice mode to MDCT music mode, the audio signal-rear of the final CELP frame in the time domain before switching adopts window-adding and folding process, and the overlapping nature of MDCT transforming ensures the continuity of switching. When a dual-mode en-decoder switches from MDCT music mode to CELP voice mode, the final MDCT frame before switching adopts a new window type in order to ensure there is no overlapping time domain with the first CELP frame, and the pre-coding technology ensures the continuity of switching.

The invention discloses a clustering-based blind source separation method for synchronous orthogonal frequency hopping signals. The method comprises the following steps of: acquiring M sampled paths of discrete time-domain mixed signals; obtaining M time-frequency domain matrixes of the mixed signals; preprocessing the time-frequency domain matrixes of the frequency hopping mixed signals; estimating frequency hopping moments, normalized mixed matrix column vectors and frequency hopping frequency; estimating time-frequency domain frequency hopping source signals by utilizing the estimated normalized mixed matrix column vectors; splicing the time-frequency domain frequency hopping source signals between different frequency hopping points; and recovering time-domain source signals according to time-frequency domain estimate values of the source signals. According to the method, the frequency hopping source signals are estimated only according to the received mixed signals of a plurality of frequency hopping signals under the condition of unknown channel information, and the frequency hopping signals can be subjected to blind estimation under the condition that the number of receiving antennae is smaller than that of the source signals; short-time Fourier transform is utilized, so that the method is low in computation amount; and the frequency hopping signals are subjected to blind separation, and meanwhile, a part of parameters can also be estimated, so that the method is high in practicability.

We describe a method of blind source separation for use, for example, in a listening or hearing aid. The method processes input data from multiple microphones each receiving a mixed signal from multiple audio sources, performing independent component analysis (ICA) on the data in the time-frequency domain based on an estimation of a spectrogram of each acoustic source. The spectrograms of the sources are determined from non-negative matrix factorization (NMF) models of each source, the NMF model representing time-frequency variations in the output of an acoustic source in the time-frequency domain. The NMF and ICA models are jointly optimized, thus automatically resolving an inter-frequency permutation ambiguity.

Described are techniques used in a wire diagnostics system to detect events, such as defects, that may occur within a wire or cable under test. An incident voltage signal is sent out on the wire and a measured voltage signal is obtained which includes the incident voltage and the reflected voltage. Compensation processing is performed on the measured waveform to remove unwanted reflective components. Additionally, the waveform is then subject to attenuation processing and event detection processing. Detected events, such as defects, are classified and output as results. Events are classified by parametric classification using a library of known events or faults. The library of known events or faults is previously generated using empirical analysis and modeling techniques. Additionally, joint time-frequency domain reflectometry (TFDR) techniques are described for event identification and classification for a wire under test.

Provided is a classification method for arrhythmia based on a one-dimension convolution neural-network and S transformation. The method includes the steps of pre-possessing electrocardiosignal; extracting the deep nonlinear characteristic of the electrocardiosignal by using the one-dimension convolution neural-network; extracting the time-frequency domain characteristic of the electrocardiosignalby using the S transformation; combining the deep nonlinear characteristic of the electrocardiosignal with the time-frequency domain characteristic of the electrocardiosignal, continuing to conduct characteristic learning after passing through a whole-connection layer, and obtaining the output characteristic of the whole-connection layer; conducting classification after the output characteristic of the whole-connection layer is connected to the softmax layer of the one-dimension convolution neural-network; outputting a classification result. According to the method, it is not necessary to conduct compression and bilinear interpolation on the electrocardiosignal to obtain the picture form of fixed pixel points to extract the characteristics. According to the method, in the aspect of characteristic extraction, the advantages of a deep learning characteristic and the time-frequency domain characteristic are combined to be composed into more complete characteristics, convergence can be quickened, over-fitting is controlled, and the insensitivity of the interwork to initialization weight is lowered. The accuracy rate of multiple kinds of arrhythmia identification is improved.

The invention discloses a spectral measurement method based on optical frequency combs. The measurement method is characterized in that firstly, an annular laser resonant cavity based on a phase modulator is actively modulated by use of a first optical frequency comb controllable in time domain and frequency domain so that the annular laser resonant cavity is converted into a second optical frequency comb having tiny difference in repetition frequency with the first optical frequency comb, and spectrum detection is performed on the two optical frequency combs to obtain an interference signal carrying the information of a sample to be tested, and meanwhile, frequency beating is performed on the two optical frequency combs and continuous frequency stabilized laser, respectively, the difference frequency signal of two obtained beat frequency signals is mixed with the interference signal, and a signal obtained by virtue of detection mixing is taken as a spectral signal for Fourier analysis so as to reduce the optical information of the sample to be tested. The spectral measurement method has the advantages that the error of the spectral detection due to own phase drift of a dual-optical comb system can be eliminated, and therefore, the resolution and the detection accuracy of the spectral measurement can be improved.

The invention discloses an uplink-grant-free resource allocation method, user equipment and a base station. The resource allocation method in an embodiment includes: the user equipment acquires resource pool information pre-allocated by the base station, wherein the resource pool includes a plurality of time-frequency domain resources; before uplink grant is received, the user equipment selects one or more time-frequency resources from the resource pool to realize uplink data transmission. Time delay can be effectively reduced while data transmission efficiency is improved.

An apparatus and method for high-resolution reflectometry that operates simultaneously in both the time and frequency domains, utilizing time-frequency signal analysis and a chirp signal multiplied by a Gaussian time envelope. The Gaussian envelope provides time localization, while the chirp allows one to excite the system under test with a swept sinewave covering a frequency band of interest. High resolution in detection of the reflected signal is provided by a time-frequency cross correlation function. The high-accuracy localization of faults in a wire/cable can be achieved by measurement of time delay offset obtained from the frequency offset of the reflected signal. The apparatus enables one to execute an automated diagnostic procedure of a wire/cable under test by control of peripheral devices.

The invention provides a method and device for iterative hybrid time-frequency domain block equalization of signals received via a communication channel subject to multipath interference. The equalization method includes frequency-domain equalization of blocks of received signals in a forward path, and time-domain inter-block echo correction and intra-block cyclic echo addition in the feedback path. The invention can be used for equalizing signals transmitted without cyclic prefix and subjected to multi-path interference with long delay spread.

The invention provides preamble transmission and receiving methods and devices, user equipment and a base station. The preamble transmission method comprises the following steps: determining time-frequency domain resources for transmitting preambles on an unlicensed carrier; and transmitting the preambles on the determined time-frequency domain resources. Through adoption of the preamble transmission and receiving methods and devices, the user equipment and the base station, the problem that a random access process cannot be implemented on the unlicensed carrier in the prior art is solved, and the effect of successfully performing random access on the unlicensed carrier is achieved.

The present invention provides a method for compensating transient effects in transform coding and decoding of a combined speech and audio in electronic devices by using a transform based time-frequency domain codec. The method can combine, e.g., a CELP (code excited linear prediction) type speech codec and a transform type audio codec. The invention describes a compensation method to handle the transient (e.g., from the CELP coding to the transform coding) in transform coding when the number of quantized transform coding coefficients is lower than in the output of the transform.

The invention provides a speech enhancing and frequency response compensation fusion method in a digital hearing-aid. The speech enhancing and frequency response compensation fusion method includes the steps of (1) obtaining estimated noise and initial enhanced speech with an MCRA method, respectively carrying out filtering processing on the estimated noise and the initial enhanced speech through a gammatone filter, dividing a signal into M frequency bands through the perception mechanism of the cochleas to the signal, and meanwhile obtaining a time frequency expression mode of the signal, (2) computing masking threshold values of the frequency bands through factors such as the audio masking characteristic of the human ears and the frequency band signal to noise ratios, (3) dynamically computing masking values of noise-contained speech in a time frequency domain through a hearing curve of a hearing disorder patient, and processing speech enhancing and frequency response compensation at the same time, and (4) synthesizing output speech of the heating-aid through the masking values. According to the speech enhancing and frequency response compensation fusion method, the working mechanism of the human ears is sufficiently used, the speech characteristics are kept, music noise introduced through a spectral subtraction method is eliminated, the speech intelligibility of output signals of the hearing-aid is greatly improved, and the low complexity and the low power consumption are achieved.

The invention discloses a combined adaptive resource allocation method and device for a PDCCH (Physical Downlink Control Channel). The method comprises the following steps of: determining a UE (User Equipment) dedicated PDCCH for transmitting data to single UE and a non-UE dedicated PDCCH for transmitting data to a plurality of UE in the PDCCH to be used for transmitting data in a subframe; and allocating resources to the non-UE dedicated PDCCH and the UE dedicated PDCCH from high to low according to priority respectively, wherein the resources comprise a time frequency domain resource and a power resource, and the priority of the non-UE dedicated PDCCH is higher than that of the UE dedicated PDCCH. By adopting the method and the device, the resource is preferably allocated to the non-UE dedicated PDCCH compared with the UE dedicated PDCCH, so that the non-UE dedicated PDCCH is not limited to the PDCCH allocation, and the problem of conflict between PDCCH detection performance and increase in number of supportable scheduled users is solved.

The present invention obtains a separated signal from an audio signal based on the anisotropy of smoothness of spectral elements in the time-frequency domain. A spectrogram of the audio signal is assumed to be a sum of a plurality of sub-spectrograms, and smoothness of spectral elements of each sub-spectrogram in the time-frequency domain has directionality on the time-frequency plane. The method comprises obtaining a distribution coefficient for distributing spectral elements of said audio signal in the time-frequency domain to at least one sub-spectrogram based on the directionality of the smoothness of each sub-spectrogram on the time-frequency plane, and separating at least one sub-spectrogram from said spectral elements of said audio signal using said distribution coefficient.

The invention relates an abnormal voice detecting method based on time-domain and frequency-domain analysis. The method includes computing the background sound intensity of a monitored scene updated in real time at first, and detecting and extracting suddenly changed fragments of the sound intensity; then extracting uniform filter Mel frequency cepstrum coefficients of the suddenly changed fragments; and finally using the extracted Mel frequency cepstrum coefficients of sound of the abnormal fragments as observation sequences, inputting a trained modified hidden Markov process model, and analyzing whether the abnormal fragments are abnormal voice or not according to frequency characteristics of voice. Time sequence correlation is improved when the hidden Markov process model is added. The method is combined with time-domain extraction of suddenly changed energy frames and verification within a frequency-domain range, the abnormal voice can be effectively detected, instantaneity is good, noise resistance is high, and robustness is fine.

Methods and systems for a mixed time-frequency domain compander, where the expander and compressor are applied in the frequency domain (subbands), while the limiter and the linear gain are applied in the time-domain (full band). Far-end noise reduction is achieved by adapting the expander gain to the far-end noise, near-end noise compensation is achieved by adapting the linear gain and the compressor gain to the near-end noise. The range of the linear gain section is set individually for each subband, but the linear gain is essentially applied to the full band signal via a scaling procedure. The scaling procedure first reduces the compander gain in the frequency domain by a scaling factor and then performs the reciprocal reverse scaling in the time domain. Far-end noise reduction is coupled to near-end noise compensation in order to avoid cross-modulation of the far-end noise by the near-end noise.

The invention provides a method for predicting the service life of a screw pair of a numerical control machine on the basis of a performance degradation model. The method comprises the following steps of: acquiring vibration signals, carrying out time-frequency domain analysis, extracting the sensitive characteristic data vectors of the performance degradation of the screw pair, and forming a sensitive characteristic matrix in a time-sequence manner; calculating the load Pi of the screw pair and recording the operating time ti at the same time; calculating the rated life time Lhi, the total time t' that the screw pair has run under the current working condition, and the expected residual life LDi according to Pi, and forming an expected residual life vector T of the expected residual life in a time-sequence manner; and fitting the mapping relation between the inputted sensitive characteristic matrix and the expected residual life vector by using a degradation model formed by a double-layer dynamic fuzzy neural network, and outputting the prediction result of the service life. By taking the impact on the performance degradation of the screw pair caused by the load change thereof under various working conditions of the numerical control machine into consideration, the method of the invention can achieve the prediction of the residual life when the screw pair is used, and ensure the high prediction accuracy and high value in actual application.

The invention relates to a seismic wave absorption and attenuation compensation method, and belongs to the geophysical exploration data processing technology. The method comprises the following steps: selecting one of VSP (vertical seismic profiling) initial data as reference data, carrying out generalized S-transform on the reference data, selecting sampling points as reference points, and recording the time and time-frequency spectrums of the sampling points; carrying out generalized S-transform on data of each sampling point, and dividing the time-frequency spectrum of corresponding frequency in the time-frequency spectrums of the reference points by the time-frequency spectrum of each sampling point so as to obtain an absorption and attenuation curve; determining a natural logarithm to figure out a phase compensation operator according to a formula of frequency difference of absorption and attenuation signals in a time frequency domain; and carrying out absorption and attenuation compensation and phase compensation in the time frequency domain to obtain a fine VSP wave field profile. The method has the advantages that noise can be eliminated during the process of fitting the absorption and attenuation curve; generalized S-inverse transform without energy loss is realized; signal-to-noise ratio and resolution of the data are improved after compensation; log resolution control is realized; the reference points are selected flexibly; and algorithm is simple and efficient.