127 results about "Discrete-time signal" patented technology

A typical data acquisition system takes periodic samples of a signal, image, or other data, often at the so-called Nyquist / Shannon sampling rate of two times the data bandwidth in order to ensure that no information is lost. In applications involving wideband signals, the Nyquist / Shannon sampling rate is very high, even though the signals may have a simple underlying structure. Recent developments in mathematics and signal processing have uncovered a solution to this Nyquist / Shannon sampling rate bottlenck for signals that are sparse or compressible in some representation. We demonstrate and reduce to practice methods to extract information directly from an analog or digital signal based on altering our notion of sampling to replace uniform time samples with more general linear functionals. One embodiment of our invention is a low-rate analog-to-information converter that can replace the high-rate analog-to-digital converter in certain applications involving wideband signals. Another embodiment is an encoding scheme for wideband discrete-time signals that condenses their information content.

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.

A filter bank device for generating a complex spectral representation of a discrete-time signal includes a generator for generating a block-wise real spectral representation, which, for example, implements an MDCT, to obtain temporally successive blocks of real spectral coefficients. The output values of this spectral conversion device are fed to a post-processor for post-processing the block-wise real spectral representation to obtain an approximated complex spectral representation having successive blocks, each block having a set of complex approximated spectral coefficients, wherein a complex approximated spectral coefficient can be represented by a first partial spectral coefficient and by a second partial spectral coefficient, wherein at least one of the first and second partial spectral coefficients is determined by combining at least two real spectral coefficients. A good approximation for a complex spectral representation of the discrete-time signal is obtained by combining two real spectral coefficients, preferably by a weighted linear combination, wherein additionally more degrees of freedom for optimizing the entire system are available.

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).

A parallel channel timing recovery circuit. The parallel timing recovery circuit comprises multiple prefilters receiving parallel channel outputs and providing prefilter outputs. Multiple sampling filters receive the prefilter outputs and provide multiple discrete time signal samples. A self-timing circuit has multiple inputs receiving the multiple discrete time signal samples. The self-timing circuit provides a sampling control output to the sampling filters. The sampling control output is based on a composite of the multiple discrete time signal samples. Each of the sampling filters generates a discrete time signal sample based on the sampling control output and the prefilter outputs.

Imbalance and distortion cancellation for composite analog to digital converter (ADC). Such an ‘ADC’ is implemented using two or more ADCs may be employed for sampling (e.g., quantizing, digitizing, etc.) of an analog (e.g., continuous time) signal in accordance with generating a digital (e.g., discrete time) signal. Using at least two ADCs allows for the accommodation and sampling of various signals having a much broader dynamic range without suffering degradation in signal to noise ratio (SNR). Generally, the signal provided via at least one of the paths corresponding to at least one of the respective ADCs is scaled (e.g., attenuated), so that the various ADCs effectively sample signals of different magnitudes. The ADCs may respectively correspond to different magnitude and / or power levels (e.g., high power, lower power, any intermediary power level, etc.). Various implementations of compensation may be performed along the various paths corresponding to the respective ADCs.

A method of enhancing signal tracking in a global positioning system receiver utilizing a frequency banked filter in providing code and carrier tracking loops includes acquiring a continuous time global positioning signal and separating the continuous time global positioning signal into in-phase and quadrature signals I and Q. The signals I and Q are sampled over a predetection interval (PDI) to provide discrete time signals, and the discrete time signals are used to generate a component in-phase measurement and a component quadrature measurement for each of multiple PDI segments of one PDI. For each of multiple different frequency bins, composite in-phase and quadrature measurements are generated by combining component in-phase measurements and component quadrature measurements from the PDI. Power is detected in each of the multiple different frequency bins for the PDI using the corresponding composite in-phase measurement and the corresponding composite quadrature measurement generated for the frequency bin.

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.

A filter intended to receive a discrete time signal at a sampling clock frequency, comprising a determined number, greater than 2, of filtering units, each filtering unit comprising head capacitors in a number equal to the determined number, assembled in parallel between an input terminal and the terminal of an integration capacitor; and means for connecting, in successive clock cycles in a number equal to the determined number, successively each head capacitor to the input terminal, and for then simultaneously connecting the head capacitors to the integration capacitor, and in which the successive clock cycles during which the head capacitors of a filtering unit are connected to the input terminal are offset by one clock cycle from one filtering unit to the next one.

A method and system for reducing the power to average ratio (PAR) at the transmitter after the up sampling and interpolation filter. In the time domain, Side Tone Packets Injection (STPI) system and method detects the optimal peaks that will result in having a low PAR at a sampling rate of T / K and combines an optimal binary and a PAR-lowering sequence and an upsampled, interpolated original discrete time signal at the scale of one extended symbol for multi-carrier modulation and at the scale M of symbols for single-carrier modulation. STPI does not require peaks search and processing at the scale of many time samples, does not require iterative Fast Fourier Transform (FFT) and Inverse Fast Fourier Transform (IFFT) processing thus, allowing the receiver not to perform extra demodulation.

In order to process a subband signal of a plurality of real subband signals which are a representation of a real discrete-time signal generated by an analysis filter bank, a weighter for weighting a subband signal by a weighting factor determined for the subband signal is provided to obtain a weighted subband signal. In addition, a correction term is calculated by a correction term determiner, the correction term determiner being implemented to calculate the correction term using at least one other subband signal and using another weighting factor provided for the other subband signal, the two weighting factors differing. The correction term is then combined with the weighted subband signal to obtain a corrected subband signal, resulting in reduced aliasing, even if subband signals are weighted to a different extent.

A method for I / Q mismatch calibration of a transmitter. First, a discrete-time signal is generated. Next, a corrected signal based on the discrete-time signal and a set of correction parameters Ap and Bp is obtained. Next, the corrected signal is converted to an analog corrected signal. Next, I / Q modulation is applied to the analog corrected signal and outputs a modulated signal. Next, a first, second, and third desired component measures and a first, second, and third image component measures with the first, second and third sets of the correction parameters Ap and Bp are respectively obtained from the modulated signal. Next, a fourth and fifth set of correction parameters Ap and Bp are obtained based on the first, the second, and the third desired component measures as well as the first, the second, and the third image component measures. Next, a fourth desired component measure and a fourth image component measure with the fourth set of correction parameters Ap and Bp and a fifth desired component measure and a fifth image component measure with the fifth set of correction parameters Ap and Bp are obtained from the modulated signal. Finally, a final set of the correction parameters Ap and Bp are selected from the fourth and fifth sets of correction parameters.

A digital-electronic-to-analog-optical converter, which has a structure consistent with a super-Mach-Zehnder interferometer, and which can perform the functionalities of both a Digital to Analog Converter (DAC) and a digital modulator uses a sub-Mach-Zender modulator to modulate optical wave signals propagating through its optical waveguide in a push-pull manner. The modulation performed is phase modulation realized with electrodes positioned near the optical wave guide where such electrodes carry modulation signals in digital, analog or discrete time signal format creating electromagnetic or electric fields that engage the optical wave signals traveling through the waveguide thus imparting a phase shift onto the optical wave signals. The amount of the phase shift can be implemented through the geometry of the electrodes, the length of time the modulating signal is applied, and the amplitude of the modulating signal.

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.

A filter intended to receive a discrete time signal at a sampling dock frequency, comprising a determined number, greater than 2, of filtering units, each filtering unit comprising head capacitors in a number equal to the determined number, assembled in parallel between an input terminal and the terminal of an integration capacitor; and means for connecting, in successive dock cycles in a number equal to the determined number, successively each head capacitor to the input terminal, and for then simultaneously connecting the head capacitors to the integration capacitor, and in which the successive dock cycles during which the head capacitors of a filtering unit are connected to the input terminal are offset by one dock cycle from one filtering unit to the next one.

Provided, among other things, is an apparatus for digitally processing a discrete-time signal that includes: an input line for accepting an input signal, processing branches coupled to the input line, and an adder coupled to outputs of the processing branches. First and second lowpass filters, each having a frequency response with a magnitude that varies approximately with frequency according to a product of raised functions, are included within baseband processors in such processing branches.

The invention discloses a gearbox fault detection method based on flexible time-domain averaging. The gearbox fault detection method comprises the steps of: 1, adsorbing an acceleration transducer on a bearing end cover of a gearbox to be detected; 2, acquiring vibration signals of the gearbox through data acquisition equipment to solve a frequency-domain discrete sampling value of the vibration signals; 3, calculating a continuous time expression of time-domain averaging; 4, converting the continuous time expression into a trigonometric function expansion form; 5, weighting ak to realize filtering, de-noising and order information extracting for the time-domain averaging; 6, carrying out discrete sampling to obtain average sequences of discrete time domains; and 7, observing periodical impacts occurring in the sequences obtained in 6, and judging the type and the severity of a gearbox fault. According to the invention, truncation errors are inhibited effectively, and the advantages of increasing the resolution ratio of the signals and increasing the detection efficiency for the gearbox are achieved while a de-noising effect is achieved.

A heterodyne receiver of a wireless communication system using an analog discrete-time signal processing is provided. The heterodyne receiver includes: a radio signal processing unit configured to extract a signal of a desired band from a received radio signal and convert the extracted signal into an intermediate frequency (IF) signal that is an integer multiple of a sample rate specified in a specification of the wireless communication system; a discrete-time signal processing unit configured to charge-sample the IF signal in unit of a predetermined time and perform an anti-aliasing filtering and a successive decimation on the charge-sampled signal, a final output rate according to the decimation being an integer multiple of the specified sample rate; and an analog-to-digital conversion unit configured to convert the successively-decimated analog signal into a digital signal.

The present invention relates to receiver apparatuses and methods of controlling weight adaptation in a receiver of a code multiplex telecommunications system with orthogonal spreading codes, wherein received discrete time signal samples are chip-level filtered by using a first equalising step. Additionally, the received discrete time signal samples are delayed by a time period corresponding to a data symbol and used in a second equalising step. Symbol estimates obtained from the first equalising step are non-linearly filtered and used as a desired response for the second equalising step in the following symbol period, wherein equaliser weights adapted in the second equalising step are used for the first equalising step. Alternatively, the second equalising step may be dispensed with and weight adaptation may be incorporated in a single equalising step. As an additional or alternative option, a hybrid equaliser architecture may be provided, where the above two-step equalisation is used during an active phase where a channel is allocated, while another weight updating scheme is used during an inactive phase where no channel is assigned. Thereby, detrimental effects of interference power can be reduced at low increase in complexity.

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.

The invention discloses a sine wave parameter measuring method and system in an electric power system. The sine wave parameter measuring method in the electric power system comprises sampling a sine wave signal and obtaining a sampling data sequence according to the preset signal time duration and a preset signal discrete sampling frequency; normalizing an amplitude of the sampling data sequence and generating into a sine wave signal sequence with the normalized amplitude; selecting two discrete signals being at a nearest starting zero crossing point distance from the sine wave signal sequence and two discrete signals being at a nearest finishing zero crossing point distance from the sine wave signal; converting sampling values of the selected four discrete signals into a period of the sine wave signal through a preset period calculation model; converting the period of the sine wave signal into the sine wave signal frequency. The sine wave parameter measuring method and system in the electric power system can rapidly and stably detect the sine wave signal frequency with high accuracy.

A periodically resetting integration angle demodulation device and a method using the same is disclosed, which uses a waveform multiplier and a periodically resetting integrator to modulate a continuous-time angle modulation signal into a discrete-time signal. The waveform multiplier multiplies the continuous-time angle modulation signal by a square wave signal whose frequency is integer times a carrier frequency, and then transmits the continuous-time angle modulation signal to a periodically resetting integrated circuit. The periodically resetting integrated circuit performs integration during a carrier period to generate a discrete-time angle modulation output signal. The present invention can greatly reduce the difficulty for designing an optical sensing system in the front end without limiting a modulation depth. Besides, the present invention achieves a small volume, high speed, high sensitivity, high reliability, high performance and high condition-adapting properties.

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.

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.

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.

A typical data acquisition system takes periodic samples of a signal, image, or other data, often at the so-called Nyquist / Shannon sampling rate of two times the data bandwidth in order to ensure that no information is lost. In applications involving wideband signals, the Nyquist / Shannon sampling rate is very high, even though the signals may have a simple underlying structure. Recent developments in mathematics and signal processing have uncovered a solution to this Nyquist / Shannon sampling rate bottlenck for signals that are sparse or compressible in some representation. We demonstrate and reduce to practice methods to extract information directly from an analog or digital signal based on altering our notion of sampling to replace uniform time samples with more general linear functionals. One embodiment of our invention is a low-rate analog-to-information converter that can replace the high-rate analog-to-digital converter in certain applications involving wideband signals. Another embodiment is an encoding scheme for wideband discrete-time signals that condenses their information content.

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.