International Trade English Phrases and Grammar Translation

With the frequent occurrence of international trade communication, in order to improve the quality of communication, this paper proposes a study on the translation of international trade English phrases and grammar. First, with the help of a rectangular window function, the composition principle of international trade English phrases is determined. Then, the horizontal feature aggregation point method is introduced to build a mathematical model of the characteristic identification of the English phrases. Finally, the sparse matrix representation of the source phrase is constructed to complete the extraction and preprocessing of the English phrase features. The input English sentence is converted into the output sentence, the form and POS factors of the English semantic translation are extracted, and a lemma is introduced to obtain the surface form of international trade English language factors. According to the international trade grammar analysis method, this paper decomposes the translation model, decomposes English sentences into small phrases for translation, and completes the research on international trade English phrase and grammar translation. The experimental results show that this method has high accuracy in the feature extraction of international trade English phrases, and the error rate is low, which is feasible.

Using Windowed Interpolation Method to Suppress Power Frequency Noise of Vibration Signal

Power frequency noise interference is widespread. In order to suppress power frequency noise coupled into vibration signal, windowed interpolating method was studied. Firstly, three typical window functions were compared, including rectangular window, Hanning window and six-term cosine window. Secondly, the numerical simulation method was used to analyze the influence of window function on the interpolation results of power frequency noise, finding that different window function should be chose when the spectrum spacing between power frequency noise and useful components of vibration signal is different. Finally, the windowed interpolation method was applied to actual engineering vibration signal to suppress its power frequency noise, with the result that the interpolation result of vibration signal is the most accurate with Hanning window. Numerical simulation and engineering application show that the windowed interpolation method is effective for power frequency noise suppression.

Suppressing of Power Line Artifact From Electroencephalogram Measurements Using Sparsity in Frequency Domain

Electroencephalogram (EEG) plays an important role in brain disease diagnosis and research of brain-computer interface (BCI). However, the measurements of EEG are often exposed to strong interference of power line artifact (PLA). Digital notch filters (DNFs) can be applied to remove the PLA effectively, but it also results in severe signal distortions in the time domain. To address this problem, spectrum correction (SC) based methods can be utilized. These methods estimate harmonic parameters of the PLA such that compensation signals are produced to remove the noise. In order to ensure high accuracy during harmonic parameter estimations, a novel approach is proposed in this paper. This novel approach is based on the combination of sparse representation (SR) and SC. It can deeply mine the information of PLA in the frequency domain. Firstly, a ratio-based spectrum correction (RBSC) using rectangular window is employed to make rough estimation of the harmonic parameters of PLA. Secondly, the two spectral line closest to the estimated frequency are calculated. Thirdly, the two spectral lines with high amplitudes can be utilized as input of RBSC to make finer estimations of the harmonic parameters. Finally, a compensation signal, based on the extracted harmonic parameters, is generated to suppress PLA. Numerical simulations and actual EEG signals with PLA were used to evaluate the effectiveness of the improved approach. It is verified that this approach can effectively suppress the PLA without distorting the time-domain waveform of the EEG signal.

Frequency-Modulated Continuous Wave Radar Respiratory Pattern Detection Technology Based on Multifeature

Respiratory diseases including apnea are often accompanied by abnormal respiratory depth, frequency, and rhythm. If different abnormal respiratory patterns can be detected and recorded, with their depth, frequency, and rhythm analyzed, the detection and diagnosis of respiratory diseases can be achieved. High-frequency millimeter-wave radar (76–81 GHz) has low environmental impact, high accuracy, and small volume, which is more suitable for respiratory signal detection and recognition compared with other contact equipment. In this paper, the experimental platform of frequency-modulated continuous wave (FMCW) radar was built at first, realizing the noncontact measurement of vital signs. Secondly, the energy intensity and threshold of respiration signal during each period were calculated by using the rectangular window, and the accurate judgment of apnea was realized via numerical comparison. Thirdly, the features of respiratory and heart rate signals, the number of peaks and valleys, the difference between peaks and valleys, the average and the standard deviation of normalized short-term energy, and the average and the standard deviation and the minimum of instantaneous frequency, were extracted and analyzed. Finally, support vector machine (SVM) and K-nearest neighbor (KNN) were used to classify the extracted features, and the accuracy was 98.25% and 88.75%, respectively. The classification and recognition of respiratory patterns have been successfully realized.

A Novel Method for Refocusing Moving Ships in SAR Images via ISAR Technique

As an active microwave remote sensing device, synthetic aperture radar (SAR) has been widely used in the field of marine surveillance. However, moving ships appear defocused in SAR images, which seriously affects the classification and identification of ships. Considering the three-dimensional (3-D) rotational motions (roll, pitch, and yaw) of the navigating ship, a novel method for refocusing moving ships in SAR images based on inverse synthetic aperture radar (ISAR) technique is proposed. First, a rectangular window is used to extract the defocused ship subimage. Next, the subimage is transformed into the ISAR equivalent echo domain, and the range migration and phase error caused by the identical movement of all ship scatterers are compensated. Then, the optimal imaging time can be selected by the maximum image contrast search method. Finally, the iterative adaptive approach (IAA) is used to obtain the image with high resolution. This method has satisfactory imaging performance in both azimuth resolution and image focus, and the amount of calculation is small due to the processing of subimages. Simulated data and Gaofen-3 real SAR data are used to verify the effectiveness of the proposed method.

An Efficient Destructive Interference Based on Side Lobe Suppression Method in SONAR Beamforming

A novel beamforming technique that resembles the principle of interference is proposed for sonar arrays to suppress the side lobes while the main lobe is kept intact. It uses two window functions. The first one is a rectangular function that produces a primary beam pattern. A secondary new window function is derived and its beam pattern is steered such that the null or trough of the main lobe of the new window coincides with the peak or crest of the first side lobe of the rectangular window and so on to other major side lobes. Pattern multiplication was used to get a final beam pattern. The approach is simulated and verified through a sonar array with 24 hydrophone sensors.

Exploring applications of Frozen Newton Method in the design of digital filter

Digital filters are popularly used in digital signal processing. The design of these filters can be done using different methods of which the rectangular window method and Frequency sampling methods are commonly used. Filter design using wavelet coefficients also shows better response. In this paper, we explore the use of the Frozen Newton method in improving the response of the filter designed using these methods. This iterative computing is applied considering the Taylor series expansion of the function up to the first order term called the Jacobian

The bispectrum and 21-cm foregrounds during the Epoch of Reionization

ABSTRACT Numerous studies have established the theoretical potential of the 21-cm bispectrum to boost our understanding of the Epoch of Reionization (EoR). We take a first look at the impact of foregrounds (FGs) and instrumental effects on the 21-cm bispectrum and our ability to measure it. Unlike the power spectrum for which (in the absence of instrumental effects) there is a window clear of smooth-spectrum FGs in which it may be detectable, there is no such ‘EoR window’ for the bispectrum. For the triangle configurations and scales we consider, the EoR structures are completely swamped by those of the FGs, and the EoR + FG bispectrum is entirely dominated by that of the FGs. By applying a rectangular window function on the sky combined with a Blackman–Nuttall filter along the frequency axis, we find that spectral, or in our case scale, leakage (caused by FFTing non-periodic data) suppresses the FG contribution so that cross-terms of the EoR and FGs dominate. While difficult to interpret, these findings motivate future studies to investigate whether filtering can be used to extract information about the EoR from the 21-cm bispectrum. We also find that there is potential for instrumental effects to seriously corrupt the bispectrum. FG removal using GMCA (generalized morphological component analysis) is found to recover the EoR bispectrum to a reasonable level of accuracy for many configurations. Further studies are necessary to understand the error and/or bias associated with FG removal before the 21-cm bispectrum can be practically applied in analysis of future data.