1364 results about "Signal reconstruction" patented technology

A method and apparatus for parallel and adaptive signal reconstruction from a multitude of signal measurements. Algorithms and hardware are disclosed to denoise the measured signals, to compress the measured signals, and to reconstruct the signal from fewer measurements than standard state-of-the-art methods require. A parallel hardware design is disclosed in which the methods that are described can be efficiently executed.

The invention discloses a sparse sampling and signal compressive sensing reconstruction method. The method comprises: establishing a signal sampling interval of each time, sampling point number, and the number of points recovering, establishing random sparse sampling lower than a Nyquist sampling theorem value; and designing a measurement matrix by random sampling timing sequence values, designing a transformation matrix of a sparse expression domain of signals, determining a compressive sensing matrix, and separated compressive sensing optimizing signal reconstruction in a nonlinear manner. The method is based on rationality of objective world rules, and makes full use of signal sparsity, uses transformation space to describe the signals, and establishes theoretical framework of new signal description and processing, so under the condition that information is not lost is ensured, signals are sampled by speed much lower than required speed of a Shannon's sampling theorem. Simultaneously, signals can be recovered completely, that is, sampling of signals is converted into sampling of information. The invention provides a whole set of complete method. The method can be used in one-dimensional and multidimensional signals, and can process audio frequency, videos, nuclear magnetic resonance, and other signals.

The invention discloses a method for timing and synchronizing wireless communication, a method for searching districts and a system thereof. The method fully utilizes the time domain repetitiveness of a main synchronizing signal in a 5ms period and comprises: firstly, adopting predetermined step length sliding time domain cross-correlation to realize blind timing coarse synchronization with low complexity and without local synchronizing signal reconstruction, simultaneously, using normalized correlation processing to resist strong interference, finally, realizing timing fine synchronization with high precision, and correcting receiver integer multiple residual frequency deviation simultaneously. The method can realize timing and synchronization rapidly and accurately in particular in environment with low signal to interference and noise ratio, thereby realizing district searching in a long term evolution wireless communication system. The method can realize downlink timing and synchronization when the signal quality is in the sensitivity position of a terminal receiver and in the environment with strong interference.

The invention discloses a reconstruction method of sparse signal, mainly solving the problem of low rate of raw sparse signal reconstructed from observation vectors. Utilizing the decomposability of aconstrained object function, the method decomposes the problem of optimizing the constrained object function into a series of small constrained object functions for optimization to improve the reconstruction rate, comprising a raw data acquisition part, a raw sparse signal reconstruction part and a reconstruction accuracy evaluation part, wherein the raw data acquisition part comprises raw sparsesignal generation, matrix observation and vector observation; the raw sparse signal reconstruction part mainly comprises setting unconstrained object function, deducing constrained object function, decomposing the constrained object function by a sequential minimal optimization method, calculating reconstruction signal and debiasing reconstruction signal; the reconstruction accuracy evaluation isto compare the magnitude of the error of mean square. The reconstruction method can improve the reconstruction rate on the premise of ensuring reconstruction accuracy rate and be used for solving theproblem of sparse signal reconstruction in the fields of compressed sensing and the like.

The present technology provides a robust noise suppression system which may concurrently reduce noise and echo components in an acoustic signal while limiting the level of speech distortion. An acoustic signal may be received and transformed to cochlear domain sub-band signals. Features such as pitch may be identified and tracked within the sub-band signals. Initial speech and noise models may be then be estimated at least in part from a probability analysis based on the tracked pitch sources. Speech and noise models may be resolved from the initial speech and noise models and noise reduction may be performed on the sub-band signals and an acoustic signal may be reconstructed from the noise-reduced sub-band signals.

The invention belongs to the field of wireless communication channel estimation, particularly relates to a compressed sensing wireless communication channel estimation method based on sparsity self-adapting, which includes the ssteps: (1) collecting demodulated receiving signals and calculating channel response of a pilot frequency position; (2) constructing a measurement matrix phi required by signal reconstruction; (3) calculating an association degree vector and sequencing elements of the vector; (4) calculating second difference vector of a novel association degree vector after sequencing and setting a threshold value I for judging sparsity of signals; (5) estimating sparsity S of channel impulse response; (6) comparing the threshold value I with the last element of a vector D sequentially, and a coefficient value corresponding to the first element larger than the threshold value is the estimated sparsity S of the signals; and (7) reconstructing the signals. The channel estimation method breaks a bottleneck of a traditional compressed sensing algorithm that the sparsity of the signals must be known, and signal reconstruction of sparsity self-adapting is achieved.

The invention relates to a cutter damage and abrasion state detecting method, which comprises the following steps that 1, vibration signals in the cutter cutting and grinding processes are measured; 2, the vibration signals are subjected to mode filtering calculation; 3, time-frequency wavelets of the vibration signals are subjected to classification sorting and feature extractions; and 4, the time-frequency wavelets are subjected to classification, collection and signal separation processing, various kinds of time-frequency wavelets are subjected to signal reconstruction, the kurtosis index (Cq) and the peak index (Ip) of various kinds of signals are then counted, the cutter damage and abrasion state and the machine tool operation state are detected under the dynamic distribution condition of a Cq-Iq plane according to various kinds of separation signal index parameters, and the identification detection and the quantitative early warning and forecast of the cutter damage and abrasion state are realized. Through single monitoring equipment, the detection of the cutter damage and abrasion state is realized, the signal identification stability is good, the mechanical processing production safety is ensured, the precision of processing parts is improved, and the production rate and the utilization rate of a machine tool are improved.

Reconstructing a second component signal relating to a second component of a multi-component picture from a spatially corresponding portion of a reconstructed first component signal and a correction signal derived from a data stream for the second component promises increased coding efficiency over a broader range of multi-component picture content. By including the spatially corresponding portion of the reconstructed first component signal into the reconstruction of the second component signal, any remaining inter-component redundancies/correlations present such as still present despite a possibly a priori performed component space transformation, or present because of having been introduced by such a priori performed component space transformation, for example, may readily be removed by way of the inter-component redundancy/correlation reduction of the second component signal.

The invention discloses a method for generating exciting signals in bandwidth extension, which processes narrow-band low frequency signals via frequency spectrum folding and synthesis to generate required high frequency exciting signals. The invention further provides a reconstruction method for the high frequency signals in bandwidth extension and a device thereof. The technical scheme utilizes low frequency signals to generate high frequency signals, and is based on the harmonic characteristic of low and high frequency spectrums of the signals, therefore, the method can extend speech and music signals effectively, and the frequency spectrum folding method can confirm the signal frequency spectrum continuity of high and low frequencies at joint part. Tests prove that the technical scheme is suitable for extending ultra wideband signals of 7 to 14 kHz.

The invention provides a compressed sensing synthetic aperture radar (SAR) imaging method based on fractional order fourier transformation, and belongs to the technical field of microwave imaging. For a sparse target scene, a system emits a linear frequency modulation pulse signal; by adopting a method for projecting an echo signal to a low-dimension measurement matrix, measurement data which are much smaller than those required by a Nyquist sampling principle are acquired; due to the echo signal, after a reconstruction matrix is constructed by a simplified fractional order fourier transformation domain sparse mode and a data acquisition mode, a calculated distance pulse pressure result is optimized by a compressed sensing signal reconstruction method and is subjected to distance migration correction and direction pulse pressure to obtain a target scene imaging result. By the imaging method, the measurement data amount of a target scene with a sparse characteristic can be greatly reduced; and pressure on data storage and data transmission can be effectively relieved.

The invention discloses an airplane angular rate signal reconstruction method based on unscented kalman filter. The method comprises the following steps of: (1), denoising an attitude angle measurement signal containing measurement noise through a nonlinear tracking differentiator to obtain a differential signal of an attitude angle, and constructing a virtual measurement equation; (2), constructing a state equation of a system on the basis of natural characteristics of an airplane and according to tri-axial angular rate signals and torque characteristics of the airplane; and (3), reconstructing an angular rate signal of the system by selecting the unscented kalman filter technology as the processing manner because both the state equation and the measurement equation are nonlinear and the estimation precision can be influenced by traditional operation for linearizing a nonlinear equation.

The multiple-antenna space multiplexing system using enhancement signal detection comprising: a code modulation module for coding and modulating bit information; a signal transmission module for transmitting the modulated signals; a signal reception module for receiving the signals; a signal form transform module for transforming form of a channel matrix H and the received signal vector r; a signal detection module for detecting the received signals; a signal reconstruction module for reconstructing the detection results of in the signal detection module, and obtaining a detected signal; a demodulation decoding module for demodulating and decoding the output of the signal reconstruction module, and outputting bit information. Compared with the conventional detection methods, the system performance is improved in considering the realization complexity.

The invention discloses a method for suppressing transient noise in voice, and belongs to the technical field of signal processing. The method for suppressing transient noise in voice is characterized by comprising a gamma through frequency cepstrum coefficient extraction module, a transient noise detection module and a voice signal reconstruction module, wherein the input end of the gamma through frequency cepstrum coefficient extraction module receives a voice signal containing noise, the output end of the gamma through frequency cepstrum coefficient extraction module is connected with the input end of the transient noise detection module, the output end of the transient noise detection module is connected with the input end of the voice signal reconstruction module, the input end of the voice signal reconstruction module receives the voice signal containing noise and is also connected with the output end of the transient noise detection module, and the voice signal reconstruction module outputs the voice with noise removed.

A remote control signal transfer system for transferring a remote control signal sent by a remote control toward a controlled apparatus via a transmission medium, the system including: one or more remote control signal reception devices each installed at a separate place; and one or more remote control signal reconstruction devices each installed for a separate one of the one or more controlled apparatuses. Each remote control signal reception devices subjects a remote control signal obtained from a remote control receiving section to sampling, and transmits resultant data to the transmission medium. Each more remote control signal reconstruction devices composes the remote control signals received from any one or more of the remote control signal reception devices via the transmission medium into a single composed signal, and outputs the single composed signal to the corresponding controlled apparatus via a single remote control transmitting section.

Systems and methods for communication of scaleable-coded audiovisual signals over multiple TCP/IP connections are provided. The sender schedules and prioritizes transmission of individual scalable-coded data packets over the plurality of TCP connections according to their relative importance in the scalable coding structure for signal reconstruction quality and according to receiver feedback. Low-latency packet delivery over the multiple TCP/IP connections is maintained by avoiding transmission or retransmission of packets that are less important for reconstructed media quality.

The invention relates to a signal reconstruction technical scheme for sampling with rate lower than nyquist rate. The signal reconstruction scheme comprises the following steps of: firstly, solving a transformation basic matrix (signals x to be reconstructed thereon are sparse on the transformation basic matrix), modulating the transformation basic matrix with a cutting sequence, filtering by means of a digital filter, sampling the filtered signals, then generating compressive sensing arithmetic operators, and finally obtaining reconstructed signals by solving an optimized problem through the sparse inverse transformation. The invention aims to provide the signal reconstruction technical scheme for sampling with rate lower than the Nyquist rate, satisfy the needs for people in solving the contradictions between the increasingly widening signal bandwidth as well as the increasingly quickening sampling frequency and the requirements for reducing processing time and various costs reduce the signal sampling frequency and data transmission and storage cost, further remarkably shorten the signal processing time and reduce the computational expense, and accurately reconstruct signals.

The invention provides a signal identification and classification method. The method comprises the followings steps of: carrying out noise reduction on initial data containing higher noise by utilizing a wavelet transform method, decomposing signals into high-frequency information and low-frequency information in data analysis, carrying out noise cancelling on the signals by adopting a soft thresholding method and then carrying out signal reconstruction; carrying out further decomposition on the high-frequency part which is not detailedly classified by multiscale analysis while inheriting allthe favorable time-frequency localization advantages of the wavelet transform; analyzing the signals within different frequency bands after multi-layered decomposition by utilizing the wavelet packettransform to extract out characteristic information reflecting a system state; transforming the characteristic vectors of input signals into a high-dimensional characteristic space through non-lineartransform and then solving for an optimal linear classification plane in the high-dimensional characteristic space. The invention overcomes the defects of difficult determination of a network structure, low convergence rate, requirement on large quantities of data samples during training, and the like in neural network learning and enables the neural network learning to be with the characteristics of high precision and strong real time in the aspect of practical application of engineering.

Methods, systems and computer readable media for reconstruction of target locations and amplitudes from signals received from one or more real targets in a space are provided, wherein the signals are at least one of signals received from the near-field and broadband signals. The space is modeled as a region of interest, and an array manifold matrix is calculated from signals received from hypothetical targets in the region of interest. One or more signal vectors received from the one or more real targets are reshaped into a data vector. A hypothetical target configuration is identified that, when applied to a signal model comprising the array manifold matrix, matches the data vector, a reconstruction vector is calculated. The reconstruction vector is reshaped into a reconstructed representation of the real targets in the space, and at least one of outputting the reconstructed representation for viewing by a user, and storing the reconstructed representation for later use are performed.