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126 results about "Discrete-time signal" patented technology

A discrete signal or discrete-time signal is a time series consisting of a sequence of quantities. In other words, it is a time series that is a function over a domain of integers. Unlike a continuous-time signal, a discrete-time signal is not a function of a continuous argument; however, it may have been obtained by sampling from a continuous-time signal, and then each value in the sequence is called a sample. When a discrete-time signal obtained by sampling a sequence corresponds to uniformly spaced times, it has an associated sampling rate; the sampling rate is not apparent in the data sequence, and so needs to be associated as a characteristic unit of the system.

Residue-compensating A/D converter

An analog-to-digital converter system [50D] processing an input signal, g, which can be either a discrete-time or a continuous-time signal. A first quantizer [154] generates a first digital signal, d0(k), representing the sum of the input signal, g, and a dithering signal, y0. A digital-to-analog converter [156] generates an analog feedback signal, alpha, representing accurately the first digital signal, d0(k). The DAC [156] may be linearized by the use of mismatch-shaping techniques. A filter [158] generates the dithering signal, y0, by selectively amplifying in the signal band the residue signal, r0, defined as the difference of the input signal, g, and the analog feedback signal, alpha. Optional signal paths [166][168] are used to minimize the closed-loop signal transfer function from g to y0, which ideally will be zero. An analog compensation signal, m0, which is described by a well-controlled relationship to the residue signal, r0, is extracted from the filter [158]. Ideally, the closed-loop signal transfer function from g to m0 will be zero, or at least small in the signal band. A second quantizer [160] converts the analog compensation signal, m0, into a second digital signal, dm0(k). The two digital signals, d0(k) and dm0(k), are filtered individually and then added to form the overall output signal, dg(k). The second digital filter [164] has a low signal-band gain, which implies that the sensitivity to signal-band errors caused by the second quantizer [160] will be low. The output signal, dg(k), is a highly-accurate high-resolution representation of the input signal, g. Circuit imperfections, such as mismatch, gain errors, and nonlinearities, will cause only noise-like errors having a very low spectral power density in the signal band.The invention facilitates the implementation of uncalibrated highly-linear high-resolution wide-bandwidth A/D converters [50D], e.g., for use in digital communication systems, such as xDSL modems and other demanding consumer-market products for which low cost is of the essence.
Owner:ANALOG DEVICES BV

Residue division multiplexing system and apparatus for discrete-time signals

A multiplexing system utilizes the whole transmission bandwidth without inducing interchannel interference for a linear channel with additive noise. Using the multiplexing system, the linear distortion channel is decomposed into independent linear distortion subchannels. Treating z-transforms as polynomials, a multiplexer at a receiver utilizes the Chinese remainder procedure to combine subchannel signals into a multiplexed signal to be transmitted through a single transmission channel. A demultiplexer at a receiver recovers the transmitted subchannel signals by taking residue polynomials on the factor polynomials used in the Chinese remainder procedure. The multiplexer that combines M subchannel signals of length K may be implemented by K M-point IFFT processors using 1-ej2pim / Mz-K (m=0 to M-1) as relatively prime polynomials required in the Chinese remainder procedure. Samples from the subchannel signals are arranged in K groups of M samples such that each group contains samples at the same position in the subchannel signals, M-point inverse DFTs of the arranged samples are computed for all of the groups, and finally the multiplexed signal is obtained by performing polyphase composition of the inverse DFT outputs. Reversing the process of multiplexing, the demultiplexer is implemented by K M-point FFT processors. Another class of the system is a multiplexing system using (1-ej2pim / Mr0z-1) (1-ej2pim / Mr1z-1) . . . (1-ej2pim / MrK-1z-1) (m=0 to M-1) as relatively prime polynomials, wherein ri is a non-zero complex number (i=0 to K-1). The multiplexer obtains the multiplexed signal by applying the Chinese remainder procedure recursively, starting with the subchannel signals Xm(z) regarding them as residue polynomials on mod((1-ej2pim / Mr0z-1) (1-ej2pim / Mr1z-1) . . . (1-ej2pim / MrK-1z-1)) (m=0 to M-1).
Owner:MURAKAMI HIDEO

Frequency-domain scalable coding without upsampling filters

In a method of coding discrete time signals (X1) sampled with a first sampling rate, second time signals (x2) are generated using the first time signals having a bandwidth corresponding to a second sampling rate, with the second sampling rate being lower than the first sampling rate. The second time signals are coded in accordance with a first coding algorithm. The coded second signals (X2c) are decoded again in order to obtain coded / decoded second time signals (X2cd) having a bandwidth corresponding to the second sampling frequency. The first time signals, by frequency domain transformation, become first spectral values (X1). Second spectral values (X2cd) are generated from the coded / decoded second time signals, the second spectral values being a representation of the coded / decoded time signals in the frequency domain. To obtain weighted spectral values, the first spectral values are weighted by means of the second spectral values, with the first and second spectral values having the same frequency and time resolution. The weighted spectral values (Xb) are coded in accordance with a second coding algorithm in consideration of a psychoacoustic model and written into a bit stream. Weighting the first spectral values and the second spectral values comprises the subtraction of the second spectral values from the first spectral values in to obtain differential spectral values.
Owner:FRAUNHOFER GESELLSCHAFT ZUR FOERDERUNG DER ANGEWANDTEN FORSCHUNG EV

Self-adaptive time-frequency hole detection method based on wavelet transformation

InactiveCN102546061AAccurate Cavitation DetectionTransmission monitoringFrequency spectrumResource block
The invention discloses a self-adaptive time-frequency hole detection method based on wavelet transformation. A wavelet transformation technology is adopted to self-adaptively carry out time frequency domain subsection on time continuous signals or discrete-time signals and judge whether each time frequency resource block is idle or not. The method comprises the following steps of: (1) firstly carrying out time domain segmentation on cognition user monitoring and receiving signals to ensure the occupied frequency band of each main user to be constant in the segment; (2) carrying out Fourier transformation on receiving signals of each sub time interval in the existing method to obtain the signal frequency spectrum of each sub time interval, and carrying out wavelet transformation to the frequency spectrum to detect the border of each frequency range so as to realize frequency range division; and (3) synthesizing self-adaptive time and frequency domain segmentation results in the last two steps to comprehensively analyze each time frequency resource block and judge whether the time frequency resource block is idle or not. The method disclosed by the invention realizes time domain and frequency domain self-adaptive segmentation of signals, effectively solves the contradiction between high resolution of a frequency spectrum hole of the frequency spectrum and the quick and in-time detection requirement in frequency spectrum detection, and simultaneously, is used for estimating the energy distribution of time and frequency domains of main user signals. A simulation result verifies the effectiveness of the method.
Owner:XI AN JIAOTONG UNIV

Pulse noise suppression method of power line communication system based on iteration adaptive algorithm

The invention discloses a pulse noise suppression method of a power line communication system based on an iteration adaptive algorithm. The pulse noise suppression method comprises the steps of sending a discrete time domain signal added with a cyclic prefix by a sending end; obtaining a mixed signal only including asynchronous pulse noise and colored background noise based on the discrete time domain signal which is without the cyclic prefix but with asynchronous pulse noise interference by a receiving end; obtaining a frequency spectrum of the mixed signal by utilizing the iteration adaptive algorithm; then obtaining an estimation value of the asynchronous pulse noise by adopting an inverted sequence and amplification transformation based on the mixed signal and the frequency spectrum thereof; and finally subtracting the estimation value of the pulse noise from a received signal and finishing suppression of the asynchronous pulse noise to obtain an effective signal. The pulse noise suppression method of the power line communication system based on the iteration adaptive algorithm has the advantages that the asynchronous pulse noise can be estimated and suppressed efficiently, the effective signal can be accordingly remained, and a relatively small error of mean square is obtained; and the pulse noise suppression method can be suitable for the Bernoulli Gaussian model, the Middleton class A model and the Gaussian mixture model.
Owner:NINGBO UNIV

Correction Method of Discrete Spectrum Low Frequency Components Based on Time Delay

The invention relates to a method for correcting low-frequency components in a discrete spectrum based on time delay, which is characterized by comprising the following steps: (1) dividing a discrete time signal into three equilong sections according to a certain time delay, summating each section of the time signal respectively and getting three sums; (2) utilizing the symmetry of the spectrum of the discrete time signal and utilizing a Fourier transform formula to get an expression form about the spectrum correction of the low-frequency components in the discrete spectrum; (3) combining the three sums with the expression form about the spectrum correction of the low-frequency components in the discrete spectrum for getting the frequency and the phase of the low-frequency components in the discrete spectrum; and combining with the expression form about the spectrum correction (2) according to the obtained frequency and the phase and further getting the amplitude of the low-frequency components; and (4) correcting the phase and getting the corrected value of the phase. The method is small in amount of calculation, high in calculation accuracy, simple and easy to operate and applicable to any window functions, and can improve the efficiency and the accuracy of the correction of the low-frequency components in the discrete spectrum.
Owner:BEIJING UNIV OF CHEM TECH

Pulse noise suppression method for power line communication system

The invention discloses a pulse noise suppression method for a power line communication system. The method comprises the following steps: transmitting a discrete time domain signal added with a cyclic prefix by a transmission end; acquiring a mixed signal only including asynchronous pulse noise and colored background noise by a receiving end according to a discrete time domain signal from which the cyclic prefix is removed and which carries asynchronous pulse noise interference; then, estimating a spectrum amplitude of the mixed signal by an iteratively adaptive algorithm; finding high amplitude points in the spectrum amplitude of the mixed signal through calculation of a mean value and a standard difference of the spectrum amplitude of the mixed signal and by use of a Chauvenet decision criterion; and setting a plurality of maximum amplitude values in the discrete time domain signal from which the cyclic prefix is removed and which carries the asynchronous pulse noise interference as 0 by counting the total quantity of the high amplitude points in the spectrum amplitude of the mixed signal in order to finish suppression of the asynchronous pulse noise and obtain a valid signal. The pulse noise suppression method has the advantages of high pulse noise suppression performance and relatively high robustness, and can be implemented well in the power line communication system.
Owner:安徽融兆智能有限公司

Method and system of cognitive radio spectrum sensing based on Gabor algorithm

The invention provides a method and a system of cognitive radio spectrum sensing based on a Gabor algorithm. The method of the cognitive radio spectrum sensing based on the Gabor algorithm comprises the following steps: step 101: sensing the conduction of sampling processing of detected continuous signals received by a user through the Gabor algorithm to obtain a discrete-time signal; step 102: calculating the Gabor coefficient of the discrete-time signal and obtaining the module value of the Gabor coefficient to be used as the energy of the detected signal; step 103: if the module value of the obtained Gabor coefficient is larger than a pre-set judging threshold, judging that a main user exists in the detected frequency range; if the module value of the obtained Gabor coefficient is smaller than the pre-set judging threshold, judging that no main user exists in the detected frequency range. When the Shannon principle is adopted for sampling, the Gabor algorithm is combined, and the sampling adopting the Gabor algorithm needs to meet that TOmega<=2pi or MN<=N1, T is a time sampling period and Omega is a frequency sampling period. On the basis of traditional energy detection, the Gabor algorithm is imported for improving the detection accuracy of the main user, , the method of the cognitive radio spectrum sensing based on the Gabor algorithm can effectively improve the accuracy of a detection result especially in low signal to noise ratio.
Owner:INNER MONGOLIA UNIVERSITY

Modulating signal recognition method based on complexity feature under low signal to noise ratio

The invention provides a modulating signal recognition method based on a complexity feature under low signal to noise ratio. The method comprises the following steps: extracting multi-fractal dimension features of different communication modulating signals, protruding features of different probability points in a time signal sequence so as to extract the features of different communication modulating signal types; furthermore, grouping pre-processed discrete-time signal sequences so as to simplify the computation of the multi-fractal dimension on the one hand, and translate the long time signal sequence into small sequence sections to observe and compute on the other hand, thereby performing small-range feature expression on the signal, and extracting the feature of the signal in a more refined manner; moreover, performing grey correlation processing on the extracted multi-fractal dimension feature of the unknown communication modulating signal and the computed multi-fractal dimension feature of the known communication modulating signal in a database, selecting the modulating type of the signal with large correlation degree as the modulating type of the unknown communication modulating signal, and then realizing the classification recognition of the modulating type.
Owner:SHANGHAI DIANJI UNIV
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