一种基于Lissajous扫描的图像显示算法

在激光扫描显示技术中,基于Lissajous图形的扫描显示具有扫描路径不规则的特点。为了使常见的逐行光栅扫描图像输入经过Lissajous扫描后正确输出显示,需要进行图像转换。按照一定的像素坐标和像素时序解算方法,计算出Lissajous扫描轨迹中当前显示像素与下一显示像素的坐标和时序关系,并参照解算出的扫描坐标和时序,提取原输入图像对应坐标处的像素进行输出,从而完成一幅图像的Lissajous扫描显示。利用Matlab对880*660@25 Hz分辨率图像进行仿真分析,得出了Lissajous扫描显示的图像像素坐标数据和时序数据,并统计出了两种数据的分布情况,仿真结果表明,该图像显示算法能准确有效地完成光栅扫描图像到Lissajous扫描的显示转换。

Application of Geodetic Receivers to Timing and Time Transfer

Two methods for smoothing pseudorange observable by Carrier and Doppler are discussed. Then the procedure based on the RINEX observation files is tested using the Ashtech Z-XII3T geodetic receivers driven by a stable external frequency at UNSO. This paper proposes to adapt this procedure for the links between geodetic receivers, in order to take advantage of the P codes available on L 1 and L 2. This new procedure uses the 30-second RINEX observations files, the standard of the International GPS Service (IGS), and processes the ionosphere-free combination of the codes P 1 and P 2; the satellite positions are deduced from the IGS rapid orbits, available after two days.

基于差分注意力的时空小波分析视频预测算法

针对视频预测中空间结构信息细节和时序运动依赖关系难以准确预测的问题,受人类视觉过程的启发,提出一种基于差分注意力机制的时空小波分析视频预测算法.首先利用时空小波分析模块对视频内容进行多频分解,增强模型对于高频细节信息以及过程性运动的理解能力;然后利用差分注意力机制指导模型更高效、合理地分配注意力资源,提升对瞬时运动特征的表达能力.在KTH, Cityscapes, BAIR, KITTI, Caltech Pedestrian数据集上的实验结果表明,所提算法在PSNR, SSIM, LPIPS评价指标上取得了比已有算法更优异的效果;同时,可视化的对比也表明所提算法的预测结果更加清晰.

Estimation of structural modal parameters by fourier transform with an optimal window

An adaptive Fourier Transform （FT） with an optimal window has been proposed for the time-frequency analysis of nonstationary time series. The method allows for a good estimation of both frequency and amplitude of the spectrum and can be easily applied to the general case of time-varying signals. The evaluation of the proposed approach has been performed on measured time-varying signals from a suspension bridge model and a steel frame model whose data have the typical non-stationary characteristics. The numerical results show that the proposed approach can overcome some of the difficulties encountered in the classic Fourier transform technique and can achieve higher computation accuracy.

Wavelet matrix transform for time-series similarity measurement

A time-series similarity measurement method based on wavelet and matrix transform was proposed,and its anti-noise ability,sensitivity and accuracy were discussed. The time-series sequences were compressed into wavelet subspace,and sample feature vector and orthogonal basics of sample time-series sequences were obtained by K-L transform. Then the inner product transform was carried out to project analyzed time-series sequence into orthogonal basics to gain analyzed feature vectors. The similarity was calculated between sample feature vector and analyzed feature vector by the Euclid distance. Taking fault wave of power electronic devices for example,the experimental results show that the proposed method has low dimension of feature vector,the anti-noise ability of proposed method is 30 times as large as that of plain wavelet method,the sensitivity of proposed method is 1/3 as large as that of plain wavelet method,and the accuracy of proposed method is higher than that of the wavelet singular value decomposition method. The proposed method can be applied in similarity matching and indexing for lager time series databases.

Wavelet Analysis in Volcanology： The Case of Phlegrean Fields

The Phlegrean Fields are an area in the west of Naples （Italy）, with a huge interest in geophysical community being a volcanic caldera among the most dangerous in the world. Various techniques of monitoring exist. Among all, the control of ground deformations and variations in sea level has considerable importance. Time series of ground deformation and tidal data in this area have been analysed to highlight these important geophysical features and these results are compared with those obtained from similar data in other time periods. With regard to first mentioned, tiltmetric data have been analysed. These ones come from the tiltmeter network sited in Pozzuoli. Instead, the tidal data come from the tide gauge in Pozzuoli. Data have been analysed by means of a wavelet approach, using a Continuos Wavelet Transform and using, as so-called ＂Wavelet Mother＂, a Gabor-Morlet wavelet. For each time series, the principal harmonic constituents result： lunar semidiurnal （M2）, solar semidiumal （S2） and lunar diurnal （K1）. Other harmonic constituents, having frequencies higher than 1/hour, are present.These last ones could be interpreted as seiches and they could be linked up with generation of discrete plumes of rising magma. Frequencies at which there is the occurrence of these seiches are in agreement with previous studies.

On temporal-spatial distribution of backscatter coefficients over China determined by TOPEX/Poseidon mission

This paper deals with the backscatter coefficients known as sigma0 at Ku band and C band based on the GDR-M (Merged Geophysical Data Record) of TOPEX/Poseidon (T/P) through Jan.1993 to Dec.2004 over land surface of China.After smoothing and interpolating the backscatter coefficients for both bands, we achieve the 5′×5′ grid data and the time series of backscatter coefficients in 12 years.The spatial distribution of sigma0 over typical areas (wetland, desert, mountainous area, agriculture base, etc.) of Chinese territory is analyzed and discussed.The fast Fourier transformation (FFT) is used to detect the cycles of seasonal variations of sigma0 time series and gives that the annual period is the major cycle.Meanwhile a semiannual period is also found in some places.We use the least squares method on both periods and find that the amplitude of annual period is obviously greater than that of semi-annual period.The relationship among the anomalousness of time series, variations of environment and climate change, and the serious natural calamity (flood, drought) is also discussed.Data of topography slope extracted from SRTM are used to do correlation analysis with the backscatter coefficients in parts of China to quantify the impact of slope on backscatter coefficients in Ku and C bands, and the results show that they all have a negative correlation but the magnitudes are different in different places with different coverages.Such as the area of Liaoning and Jilin has the maximum correlation -0.56, the Taklimakan Desert has the minimum correlation -0.11, and the other places commonly have correlations in (-0.3, -0.5).

Smoothing Non-Stationary Time Series Using the Discrete Cosine Transform

This paper considers the problem of smoothing a non-stationary time series(having either deterministic and/or stochastic trends) using the discrete cosine transform(DCT).The DCT is a powerful tool which has found fruitful applications in filtering and smoothing as it can closely approximate the optimal Karhunen-Loeve transform(KLT).In fact,it is known that it almost corresponds to the KLT for first-order autoregressive processes with a root close to unity:This is the case with most economic and financial time series.A number of new results are derived in the paper:(a) The explicit form of the linear smoother based on the DCT,which is found to have time-varying weights and that uses all observations;(b) the extrapolation of the DCT-smoothed series;(c) the form of the average frequency response function,which is shown to approximate the frequency response of the ideal low pass filter;(d) the asymptotic distribution of the DCT coefficients under the assumptions of deterministic or stochastic trends;(e) two news method for selecting an appropriate degree of smoothing,in general and under the assumptions in(d).These findings are applied and illustrated using several real world economic and financial time series.The results indicate that the DCT-based smoother that is proposed can find many useful applications in economic and financial time series.