54 results about "Energy (signal processing)" patented technology

The invention discloses a bistatic ISAR imaging method based on weighted L1 norm constraints, which belongs to the technical field of radar signal processing, and adopts the following steps: Step 1. Establishing a bistatic ISAR imaging echo model to obtain full aperture echo data; Step 2. Construct a sparse basis matrix to obtain the sparse representation of the full aperture echo data, construct an observation matrix to obtain the sparse aperture echo data, and establish a bistatic ISAR sparse aperture imaging model based on compressed sensing; Step 3. Set each pixel of the target to be sparse The same distribution is subject to Laplace prior, and the maximum posterior probability estimation function of the target image is established by Bayesian criterion, which is approximated as a weighted L1 norm constraint solving problem; step 4, using the Cauchy-Newton algorithm for weighted L1 norm constraint The solution of the optimization problem realizes the reconstruction of the target image; the invention can make better use of the energy accumulation and structural characteristics of the target, and is beneficial to improve the imaging quality.

The invention relates to a dynamic extrapolation method of a bandwidth-limited signal, which belongs to the technical field of signal processing. The invention solves the problems of low efficiency of the traditional extrapolation method when the observation time is relatively small and low reliability of the traditional extrapolation method when the iterative filter bandwidth is larger than the signal bandwidth. The present invention improves the extrapolation accuracy when the initial energy of the observation signal is relatively small by treating the extrapolation signal segmented and sequentially extrapolating, and solves the problem of the traditional Gerchberg-Papoulis extrapolation algorithm (referred to as GP algorithm) when the observation time is relatively small. Low-efficiency extrapolation problem, and the low-reliability extrapolation problem when the iterative filter bandwidth is greater than the signal bandwidth, when the computational complexity is fixed, under the requirements of a certain extrapolation performance index, the dynamic extrapolation method of the present invention can improve the GP algorithm The effectiveness of the GP algorithm improves the reliability of the GP algorithm in scenarios where the signal bandwidth is uncertain within a certain range. The invention can be applied to the technical field of signal processing.

The invention provides a method for solving event-related potential waveform diagrams based on sparse modeling. Including: data preprocessing, de-drying, framing and energy normalization; sparse dictionary learning, dictionary initialization, sparse modeling, dictionary learning and convergence judgment; waveform dictionary clustering; waveform dictionary property determination. The advantage of the present invention is that: the ERP waveform is acquired for the inherent event-related potential activity pattern in the data instead of the label given by the cognitive experiment, not only can process the EEG data in the experimental environment, but also can process the acquisition in the real environment without labels EEG data with better universality and practicability. In addition, the use of a signal processing method for single-shot and single-frame data processing can effectively improve the flexibility of EEG analysis and processing, and it also has a significant application prospect in the field of brain-computer interface.

The least squares channel estimation method based on the minimum energy wavelet framework, the steps are as follows: use the LS algorithm for preliminary channel estimation; perform energy normalization processing on the preliminary channel estimation results to obtain a normalized sequence; use the minimum energy wavelet framework to normalize The decomposed sequence is decomposed into the first layer and the second layer to obtain the decomposed sequence; based on the hard threshold function, the decomposed sequence is denoised; the wavelet tower reconstruction algorithm is used to reconstruct the signal, and the reconstructed new signal is reversed. The energy is normalized and calculated to obtain the final estimated value. The present invention adds a signal processing link based on the minimum energy wavelet frame on the basis of the preliminary channel estimation result obtained by the traditional LS algorithm, and can eliminate the error components in the estimation result obtained by the LS algorithm, thereby improving the accuracy of channel estimation. Moreover, the wavelet tower decomposition and reconstruction algorithm has low computational complexity and is easy to implement in engineering, laying the foundation for subsequent channel equalization and decoding performance improvement.

The invention discloses a signal processing method and system for blast furnace lining impact echo detection. The material of a detected object is subjected to wave velocity calibration through a timedifference ultrasonic method, calibration wave velocity information is obtained, empirical modal decomposition is conducted on impact echo signals, and an intrinsic model component is obtained; on the basis of the intrinsic model component, the impact echo signals are filtered to obtain filtered signals and energy operators based on the filtered signals; and the filtered signals are classified, and on the basis of a classification result and the wave velocity information, thickness information of the innermost layer of a blast furnace lining is obtained. The technical problem that in the prior art, elastic waves generate the aliasing effect during propagation in a non-uniform layered medium and accordingly the deviation of an erosion state detection result of the blast furnace lining is large is solved. By denoising the collected impact echo signals and further utilizing the energy operators to classify the filtered signals, echoes of various types can be effectively distinguished, sothat corresponding features of a boundary surface are accurately extracted, and finally the thickness information of the innermost layer of the blast furnace lining is accurately extracted.