Vibration-assisted vat photopolymerization for pixelated-aliasing-free surface fabrication

Mask image projection-based vat photopolymerization(MIP-VPP)offers advantages like low cost,high resolution,and a wide material range,making it popular in industry and education.Recently,MIP-VPP employing liquid crystal displays(LCDs)has gained traction,increasingly replacing digital micromirror devices,particularly among hobbyists and in educational settings,and is now beginning to be used in industrial environments.However,LCD-based MIP-VPPsuffers from pronounced pixelated aliasing arising from LCD’s discrete image pixels and itsdirect-contact configuration in MIP-VPP machines,leading to rough surfaces on the 3D-printed parts.Here,we propose a vibration-assisted MIP-VPP method that utilizes a microscalevibration to uniformize the light intensity distribution of the LCD-based mask image on VPP’s building platform.By maintaining the same fabrication speed,our technique generates asmoother,non-pixelated mask image,reducing the roughness on flat surfaces and boundary segments of 3D-printed parts.Through light intensity modeling and simulation,we derived an optimal vibration pattern for LCD mask images,subsequently validated by experiments.We assessed the surface texture,boundary integrity,and dimensional accuracy of componentsproduced using the vibration-assisted approach.The notably smoother surfaces and improved boundary roughness enhance the printing quality of MIP-VPP,enabling its promisingapplications in sectors like the production of 3D-printed optical devices and others.

An Anti-aliasing Algorithm Suitable to Map Publishing Symbol

On the basis of analysis of various algorithms, an anti-aliasing algorithm called brush method was presented, which is suitable to map publishing symbol. After introducing the basic principle and implementation of brush method in detail, the result and efficiency were evaluated through experiments.

Geotechnical engineering blasting:a new modal aliasing cancellation methodology of vibration signal de-noising

In the present study of peak particle velocity(PPV)and frequency,an improved algorithm(principal empirical mode decomposition,PEMD)based on principal component analysis(PCA)and empirical mode decomposition(EMD)is proposed,with the goal of addressing poor filtering de-noising effects caused by the occurrences of modal aliasing phenomena in EMD blasting vibration signal decomposition processes.Test results showed that frequency of intrinsic mode function(IMF)components decomposed by PEMD gradually decreases and that the main frequency is unique,which eliminates the phenomenon of modal aliasing.In the simulation experiment,the signal-to-noise(SNR)and root mean square errors(RMSE)ratio of the signal de-noised by PEMD are the largest when compared to EMD and ensemble empirical mode decomposition(EEMD).The main frequency of the de-noising signal through PEMD is 75 Hz,which is closest to the frequency of the noiseless simulation signal.In geotechnical engineering blasting experiments,compared to EMD and EEMD,the signal de-noised by PEMD has the lowest level of distortion,and the frequency band is distributed in a range of 0-64 Hz,which is closest to the frequency band of the blasting vibration signal.In addition,the proportion of noise energy was the lowest,at 1.8%.

Identification of indoor multi-component pollution gas aliasing peak based on JADE

Monitoring indoor harmful gas can obtain the infrared spectra of mixed harmful gases.Since the absorption bands of mixed gases overlap and their qualitative and quantitative analyses are not easy,feature extraction method based on joint approximative diagonalization of eigenmatrix（JADE）is proposed.By fully mining the hidden information of original data and analyzing higher-order statistics information of the data,each substance spectrum in the mixed gas can be accurately distinguished.In addition,a multi-dimensional data quantitative analysis model of the extracted independent source is established by using support vector machine（SVM）based on regular theory.The experimental results show that the correlation coefficients of the components of mixed gases is above 0.999 1by quantitative analysis,which verifies the accuracy of this feature extraction method.

A Velocity Dealiasing Scheme for C-band Weather Radar Systems

A dealiasing algorithm for radar radial velocity observed by C-band Doppler radars is presented as an extension of an existing S-band dealiasing algorithm. This has operational significance in that many portable and many commercial broadcast radars, as well as approximately one half of the Chinese weather radar network （CINRAD）, are C-band radars. With a wavelength of about 5 cm, the Nyquist interval of C-band radars is just about one half that of S-band radars （wavelength of about 10 cm） and thus has more velocity folding. The proposed algorithm includes seven modules to remove noisy data, find the starting radials, dealias velocities, and apply least squares error checking in both the radial and azimuth directions. The proposed velocity dealiasing method was applied to one widespread rain case and three strong convective cases from radars operating in China. It was found that, on average, 92.95% of the aliased radial velocity data could be correctly de-aliased by the algorithm, resulting in 96.65% of the data being valid.

Truncation and aliasing errors for Whittaker-Kotelnikov-Shannon sampling expansion

Let B^pΩ, 1 ≤ p 〈 ∞, be the space of all bounded functions from Lp（R） which can be extended to entire functions of exponential type Ω. The uniform error bounds for truncated Whittaker-Kotelnikov-Shannon series based on local sampling are derived for functions f ∈ B^pΩ without decay assumption at infinity. Then the optimal bounds of the aliasing error and truncation error of Whittaker-Kotelnikov-Shannon expansion for non-bandlimited functions from Sobolev classes L/（Wp（R）） are determined up to a logarithmic factor.

Aliasing-free high resolution imaging of fast rotating targets with narrowband radar

Narrowband radar has been successfully used for high resolution imaging of fast rotating targets by exploiting their micro-motion features.In some practical situations,however,the target image may suffer from aliasing due to the fixed pulse repetition interval(PRI)of traditional radar scheme.In this work,the random PRI signal associated with compressed sensing(CS)theory was introduced for aliasing reduction to obtain high resolution images of fast rotating targets.To circumvent the large-scale dictionary and high computational complexity problem arising from direct application of CS theory,the low resolution image was firstly generated by applying a modified generalized Radon transform on the time-frequency domain,and then the dictionary was scaled down by random undersampling as well as the atoms extraction according to those strong scattering areas of the low resolution image.The scale-down-dictionary CS(SDD-CS)processing scheme was detailed and simulation results show that the SDD-CS scheme for narrowband radar can achieve preferable images with no aliasing as well as acceptable computational cost.

Anti-aliasing wavelet packet method for harmonic detection

A novel anti-aliasing wavelet packet transform method for harmonic detection is proposed. Aiming at the low measurement precision and poor robustness which exists in the former traditional wavelet methods for lack of the aliasing_reduction scheme, an optimal interpolation wavelet packet filter is designed according to new optimal criteria. First, the limitation of anti-aliasing on the traditional wavelet filter bank is analyzed. Second, the designed optimal interpolation filters axe denoted, and then the solution algorithm is given. This devised wavelet packet filter can seek a reasonable balance between signal preservation and aliasing reduction; it overcomes the inherent bug of traditional wavelet transforms, which rooted from just only concerning total aliasing cancellation but not aliasing-reduction in decomposition. Simulation and several comparative results indicate that the proposed method can effectively eliminate aliasing and precisely extract harmonic information.

On the aliasing error in a class of bidimensional wavelet subspaces

This paper addresses the aliasing error in multiresolution analysis associated with a 2× 2 dilation expression of the Fourier transform of the aliasing error optimal L^2（R^2）-norm estimation of the aliasing error. the setting of a class of bidimensional matrix of determinant ±2. The explicit is established, from which we obtain an

Cancellable Multi-Biometric Template Generation Based on Arnold Cat Map and Aliasing

The cancellable biometric transformations are designed to be computationally difficult to obtain the original biometric data.This paper presents a cancellable multi-biometric identification scheme that includes four stages:biometric data collection and processing,Arnold’s Cat Map encryption,decimation process to reduce the size,and finalmerging of the four biometrics in a single generated template.First,a 2D matrix of size 128×128 is created based on Arnold’s Cat Map(ACM).The purpose of this rearrangement is to break the correlation between pixels to hide the biometric patterns and merge these patterns together for more security.The decimation is performed to keep the dimensions of the overall cancellable template similar to those of a single template to avoid data redundancy.Moreover,some sort of aliasing occurs due to decimation,contributing to the intended distortion of biometric templates.The hybrid structure that comprises encryption,decimation,andmerging generates encrypted and distorted cancellable templates.The simulation results obtained for performance evaluation show that the system is safe,reliable,and feasible as it achieves high security in the presence of noise.

Aliasing Error of Sampling Theorem

Let f∈Lpr（R）,1【p【∞,r∈N),the bound for aliasing of function fin Lp—metricesis given in[1].From embedding Theorem and Stein inequality,it follows,that if f∈Lpr（R）,1【p【∞,then f∈Lqr（R）,1【p【q≤∞ and f（k）∈Lp（R）∩Lq（R）,k=0,1,…,r-1.In this paper,we con-tinued Fang’s work in[1],and obtain the bound for aliasing error of function f∈Lpr（R）,1【p【∞,inLq-metrices（p≤q≤∞）.And the order is exact when 1【p≤q≤2.

The impact of frequency aliasing on spectral method of measuring T wave alternans

In this paper we investigate frequency aliasing in spectral method of measuring T wave alter-nans, which may lead a high false positive rate. Microvolt T wave alternans(TWA) has been evaluated as a means of predicting occurrence of ventricular tachyarrhythmia events and its association with the genesis of ventricular ar-rhythmias has been demonstrated. Nowadays, spectral method is one of the most widely used procedures for measurement of microvolt TWA. In our study, based on the sampling theory, the alternans frequency 0.5 cycles/beat, at which the power of the spectrum is used to calculated the Valt and K score (these two parameters indicate the TWA), is equal to the nyquist frequency. Thus this generates frequency aliasing which will make the power at the alternans frequency (P0.5) be two times of the real magnitude of the original spectrum amplitude. With the assump-tion that the noise spectrum follows the normal distribution, in spectral method of measuring T wave alternans, the measuring standard K score>3 to consider the T wave alternans sig-nificant is only with a p<0.133. By change the standard to K score>6 can solve this problem and make the p value to p<0.0027.

Feasibility study on application of satellite formations for eliminating the influence from aliasing error of ocean tide model

Currently,aliasing error of temporal signal model becomes the main factor constraining the accuracy of temporal gravity field.In provision of three types of satellite formations,i.e.,GRACE-type,Pendulum-type and n-s-Cartwheel-type,which are suitable for gravity mission and composed of observation in different directions,here we design two cases and conduct a simulation experiment on the feasibility to apply satellite formations for eliminating the influence from the aliasing error of ocean tide models.The result of our experiment shows that,when the aliasing error is disregarded,n-s-Cartwheel formation can provide the best conditions for gravity field determination,which,compared with GRACE-type,can improve the accuracy by 43%.When aliasing error of the ocean tide model acts as the main source of error,the satellite formation applied in dynamic method for gravity field inversion cannot eliminate aliasing or improve the accuracy of gravity field.And due to its higher sensitivity to the high-degree variation of gravity field,the Cartwheel-type formation,which includes the radial observation,can result in the gravity field containing more high-frequency signals for the ocean tide model error,and lead to a dramatically larger error.

Whittaker-Kotelnikov-Shannov type sampling theory and the estimates of aliasing error

Let E be a finite interval or real axis R and denote by Lp（E）, 1≤p≤∞, the classical Lebesque space with usual norm. Let r∈N and denote by Lpr（R）, 1≤p≤∞, the subspace of functions f in Lp（R） for which the （r-1）-th derivative exists and is locally absolutely continuous on R and ||ff||P（R） is finite. Further

Aliasing Errors in Parallel Signature Analyzers

A Linear Feedback Shift Register (LFSR)can be used to compress test response data as a Signature Analyzer(SA). Parallel Signature Analyzers (PSAs) implemented as multiple input LFSRs are faster and re- quire less hardware overhead than Serial Signature Analyzers (SSAs)for compacting test response data for Built-In Serf-Test (BIST)in IC or hoard-testing environments. However, the SAs are prone to aliasing errors because of some specific types of error patterns. An alias is a faulty output signature that is identical to the fault-free signature. A penetrating analysis of detecting capability of SAs depends strongly on mathematical manipulations, instead of being aware of some special cases or examples. In addition , the analysis should not be restricted to a particular structure of LFSR, but be appropriate for various structures of LFSRs. This pa- per presents necessary and sufficient conditions for aliasing errors based on a complete mathematical descrip- tion of various types of SAs. An LFSR reconfiguration scheme is suggested which will prevent any aliasing double errors. Such a prevention cannot be obtained by any extension of an LFSR.

Roll Eccentricity Compensation Based on Anti-Aliasing Wavelet Analysis Method

Roll eccentricity is an important factor causing thickness variations during hot strip rolling and might define the limit of strip thickness control accuracy. An improved multi-resolution wavelet transform algorithm was proposed to compensate for the roll eccentricity. The wavelet transform method had good localization characteristics in both the time and frequency domains for signal analysis; however, the wavelet method had a frequency-aliasing problem owing to the less than ideal cut-off frequency characteristics of wavelets. This made its component reconstruction of an inaccurate signal. To eliminate inherent frequency aliases in the wavelet transform, fast Fourier transform （FFT） and inverse fast Fourier transform （IFFT） were combined with the Mallat algorithm. This synthesis was described in detail. Then, the roll eccentricity component was extracted from rolling force signal. An automatic gauge control （AGC） system added with a multi-resolution wavelet analyzer was designed. Experimental results showed that the anti-aliasing method could greatly restrain the inverse effect of eccentricity and the thickness control accuracy was improved from ±40 μm to ±15 μm.

Comb-Based Filter Design Using Sharpening Technique and Certain Palindromic Polynomial

This paper presents a novel approach to improve aliasing rejection in comb-based decimation filters. The method is established on certain palindromic polynomials with all zeros on the unit circle and the sharpening technique. As a result, aliasing rejection and the passband characteristic are improved. The method is illustrated with various examples and compared with the methods from the literature. .

Principle and application of high density spatial sampling in seismic migration

To avoid spatial aliasing problems in broad band high resolution seismic sections, I present a high density migration processing solution. I first analyze the spatial aliasing definition for stack and migration seismic sections and point out the differences between the two. We recognize that migration sections more often show spatial aliasing than stacked sections. Second, from wave propagation theory, I know that migration output is a new spatial sampling process and seismic prestack time migration can provide the high density sampling to prevent spatial aliasing on high resolution migration sections. Using a 2D seismic forward modeling analysis, I have found that seismic spatial aliasing noise can be eliminated by high density spatial sampling in prestack migration. In a 3D seismic data study for Daqing Oilfield in the Songliao Basin, I have also found that seismic sections obtained by high-density spatial sampling （10 ×10 m） in prestack migration have less spatial aliasing noise than those obtained by conventional low density spatial sampling （20 × 40 m） in prestack migration.

混叠和抗混叠技术

操作Photoshop或其它图像处理软件时经常要对是否启用Anti-aliasing这一功能作出选择。Aliasing一词指数字图像信号的频率混叠现象,它可能因原稿数字化时采样间隔过大而产生,也可能产生于图像的重新采样操作(比如放大或缩小图像,选择部分图像后的裁剪或粘贴操作)。此外。

基于Alias的自由曲面逆向造型设计

介绍了Alias逆向造型工具的特点和工作流程及其曲面造型技术.通过儿童安全座椅局部点云的反求设计,阐述运用Alias进行复杂曲面重建及造型的过程.通过曲面拓扑结构的合理划分,解决复杂曲面的重建很难用简单特征或特征曲线拟合的曲面来实现这一难题.研究表明,Alias直接建模的灵活性和高精确度,对于缩短产品开发周期、保证产品质量具有重大意义.