Optimizing Delay Time Interval by the Means of Time - Energy Analysis Based on Wavelet Transform

In millisecond blast engineering,the key to achieving millisecond blast is to ascertain reasonable delay time interval.Firstly,the authors make use of time-energy density analysis based on wavelet transform,and get the real delay time by identifying the blast moment of short-delay detonators.Secondly,every sub-signal is separated from measured millisecond blast vibration signal by time-frequency domain transform techniques.Lastly,the Optimized delay time interval is obtained by comparing the superposition effect of sub-signal in different delay time interval.The effectiveness of the proposed method is verified with time-energy density analysis of millisecond blasting vibration signals in an underground project.It shows a high theoretical and practical value,and establishes a theoretical and technical foundation for the study of controlling and forecasting blast vibration damage.     

Parallel Algorithm of Structural Optimization Based on Space time Transform

In this paper an attempt has been practised to introduce parallel techniques into the structural optimization.Based on space time transform five approaches for parallel computation of structural optimization have been presented.This paper has also pointed out the problems originated from large scale systems of structural optimization (LSSO) and put forward the technical line of design of LSSO.     

A Numerical Algorithms of Fractional Fourier Transform

Signal and it's Fourier transform can reflect the info of time domain and frequence domain independently. As a usually math tool, Fourier transform is using in math, physical and engineering field widely. A new tool for signal analysis,which is named Fractional Fourier transform(FRFT), is introduced. It is interpreted in view of the classic Fourier transform. It is important to study the numerical algorithms of FRFT, because usually the FRFT can not be given to a analytical expression. A numerical algorithms of FRFT is given. It is possible to separate the distortion from the simple Gaussian signal on which a chirp distortion has been superimposed by using fractional transform.     

Speedy Recognition of Noise in Real Time Signal Based on Wavelet Transform

It's necessary to process position and gesture of rocket on real time within the flight of rocket. This work should base exact data. But much noise has been found in the data and the noise recognize is regarded as a focus. A speedy online arithmetic recognizing noise is proposed based on wavelet transform. The computing complexity measured by time of this arithmetic is a constant which is greatly reduces the works of calculation of wavelet transform. It can recognize the noise fast when the signal is gathered. The applications in these problems show that the effective arithmetic satisfies the needs of real time and can handle the real time data measured in other yields.     

Wavelet-Based Multiresolution Analysis to Noise Elimination

The wavelet transform is a new subject developed quickly in the past ten years Compared with Fourier transform and Gabor transform, the wavelet transform is a part of time-frequency transform, so the message can be obtained from the signals effectively. By means of the fractionized multiresolution analysis to the signals, many problems unalbe to be solved by Fourier tranform have been solved in this way.Based on the fact that the maxima of the noise wavelet transform reduces dramatically with the increase of the scale, we obtain the result that this way is more advanced than the Fourier transform multiresolution analysis to the noise elimination.     

Systems Analysis Based on Continuous Wavelet Transform

The linear time invariant vibration system is analyzed by Continuous Wavelet Transform(CWT),the relationship of wavelet transform of output signal with the pulse response of system and input signal is put forward.As an exapmle,the wavelet transform of the output signal of system with single degree of freedom is calculated and compared with the direct wavelet transform result of the actual output signal,it shows that the two results are in complete agreement.     

Multi scale and multi orientation features for image de noising

An adaptive algorithm for image de noising is proposed based on the multi scale and multi orientation features. The coefficients in different scales and different directions are obtained by image decomposition using the nonsubsampled contourlet transform. Then thresholds functions are adaptively set with these coefficients. The texture of the image information is introduced by using the mean of decomposition scale and the energy of regional. The greater the energy, the more information of the texture while the same decomposition scales, the smaller the threshold is set. On the contrary, the greater the threshold is set. After the de noising and then reconstruction of these coefficients, image de noising is implemented. Compare to the wavelet transform threshold and contourlet transform threshold, the nonsubsampled contourlet transform pick up the image detail better and improve the quality of the image.     

Multiresolution Wavelet Transform for Detection of EEG Abnormal Rhythms

The signal of brain activity is a non-stationary random signal including lots of physiology and disease information, which is of important action for doctors to judge pathological changes in brain. So the analysis and process of the EEG signals are always attended. In this paper, the authors take account of the time-frequency localization of wavelet transform and use multiresolution wavelet transform to detect EEG abnormal rhythms. The signals of different scales after EEG signals are transformed by multiresolution wavelet transform not only reflect the frequency information of the signals, namely the more great scale is the lower of the frequency of the signals,but also reflect the time information of the signals, namely EEG state at that time. The test results indicate that the abnormal rhythms of the EEG signals can be detected effectively if right wavelet basis is selected.     

Audio blind watermarking scheme combined DWT DCT QR

In order to protect the copyright of digital audio and video in Internet, we propose a novel audio blind watermarking scheme combined discrete wavelets transform, discrete cosine transform, QR decomposition and audio characteristics. In this algorithm, the audio are split into blocks, and each block are decomposed on two dimensional discrete wavelet transform (DWT), then the approximate sub band coefficients are decomposed on discrete cosine transform (DCT), and the first quarter of the DCT coefficients are decomposed on QR decomposition and get a triangle matrix. At last, the watermarking information is embedded into the triangle matrix. The experiments show that the algorithm can get better balance between transparency and robustness of watermark, and it has strong robustness against the common audio signal processing such as additive white Gaussian noise, re sampling, re quantization, low pass filter, MP3 compression and cutting replacement.     

A Research on the Characteristics of Mexican-hat Mother Wavelet Used in Optic Realization

The Mexican hat mother wavelet used in optic realization is analysed. Its characteristics on time frequency domain localization, accurate reconstruction condition, regularity order and orthonormality are discussed. The error concept for the Mexican hat wavelet that the non tensor product two dimensional form of mother wavelet is obtained from the turning of its one dimensional form is corrected. The reason is explained for that the Mexican hat mother wavelet can't be used in conventional discrete wavelet transform for image data compression,but when it is used in 2 D image wavelet transform realized by optic way, it features excellent energy localization.     

A New Fast Algorithm for the Discrete Cosine Transform

We prepose a new fast algorithm for computing discrete cosine transform and its inverse on two dimensional input sizes which are powers of 2.Because the integer operation is more faster than the float operation in computer,the integer operation is used in this algorithm.Through the matrix linear transform the number of operation for multiplications and additions is reduced,so that the speed is greatly raised.This algorithm is applied to our developmented JPEG image coding,and yields very good results.     

Filtering Construct of Adaptive Filter Grou Pwith Multi-scale Decomposition

The principle and method of the adaptive filter and the filtering with wavelet transform were analyzed, and the model and method of adaptive filtering with wavelet transforms for the transient signal was established. The separated noise of signal by the multi-scale decomposition of wavelet transforms, was the input signal of adaptive filter, and accordingly the optimal filtering method of signal-noise decomposition was realized. By the adaptive filter grou Pbased on the wavelet transform, the optimal filtering to the multi-noise of signal is achieved at the same time, and the method presented in this paper has the excellent filtering capability. Examples of application demonstrate that this method presented is excellent to realize the optimal estimate to the valuable signal and noise of the transient signal in the same frequency segment.     

Filter Design of Wavelet Transform for 2-D Image

The filter design is the key to 2-D image wavelet transform. Based on the studying of image properties and 1-D wavelet theory,the authors describe a parasymmetry boundary extension method and realize 2-D discrete wavelet transform by means of 1-D wavelet transform according to correlation of adjacent pixels. Also,it is proved that the discrete wavelet transform of inverse data stream in row and the sign of discrete detail signal will be inversed,and that a filter of wavelet transform based on symmetry of bi_orthogonal filter is constructed. The test has proved the fine reconstruction and perfect SNR.     

A Virtual Wavelet Transform Analyzer for the Signal Analysis Based on the Direct Algorithm

A virtual wavelet transform analyzer for the signal analysis based on the direct algorithm is introduced so that the discrete wavelet transform and continuous wavelet transform is maken to signal in the direct algorithm. The authors first introduce the direct algorithm of the WT, which is numerical algorithm obtained from the original formula of the wavelet transform by directly numericalizing. Then some conclusions are drawn on the direct algorithm. The examples are the sampling principle and technology for the wavelets, the limitation of the scale range of the wavelets and the measures to solve the edge phenomenal in the direct algorithm of the discrete wavelet transform, and some conclusions in the direct algorithm of the continuous wavelet transform. The virtual wavelet transform analyzer for the signal analysis based on the direct algorithm explored based on these studies and combined with virtual instrument technique can make the discrete wavelet transform and continuous wavelet transform to signal with any basic wavelet. It can be applied in studying the property of any basic wavelet and learning the theory on the wavelet transform, and also in making some engineering signal analysis. In the end, the authors give some typical examples for the application of the virtual analyzer. These examples show that the analyzer can be applied in many situations.     

Transform of Orthogonal Double Complex Variables

By article \ the paper puts forward a concept of orthogonal double complex variables space. Its conformal transform and its typical form of transform are doscissed, such as three dimensional complex space square transform, space rukovski transform.     

Application of Wavelet Transform to De-noising Method

The wavelet transform is a new subject developed quickly in the past ten years. Compared with the Fourier transform, the wavelet transform is a part of time-frequency transform. The most important character is that it can be used to transform a signal into basic units at different scales and location, each unit represents a component of original signal difference from others. The wavelet transform has been proven to be a powerful and efficient tool for processing signal due to this character. This paper introduces the de-noising principles of the wavelet transform. It is proved to be an effective method by the simulating analysis.     

盐水鹅辐照保质试验研究

鹅是食草家禽,鹅肉属现代健康食品。盐水鹅在20℃的贮存条件下仅36h就会出现异味变质。介绍了通过用不同包装材料、不同辐照剂量保质处理以及对盐水鹅氨基酸影响的研究,探讨了盐水鹅辐照保质的方法,为延长盐水鹅货架期提供新途径。     

Production Planning Method for Steelmaking-continuous Casting Process Based on Time Backward and Process Simulation

Reasonable production planning effectively ensures smooth operation. According to the analysis of the characteristics of steelmaking-continuous casting production process, a production planning method for steelmaking - continuous casting process based on time backward inference method and process simulation is presented. Production plan meeting certain criteria is rapidly gained by time backward inference method, and is regarded as input of simulation model in steelmaking process. Considering time randomicity in production process and transporting equipment restriction, production plan meeting more restrictive conditions, such as no equipment conflict, continuous casting, and etc, is acquired through simulating. It assures that the plan is carried out in practice. The instance demonstrates the feasibility of the method.     

Binary phase only filter based watermarking combined with discrete wavelet transform

The binary phase only filter (BPOF) based digital image watermarking combined with a discrete wavelet transform (DWT) was proposed. Firstly, the DWT transform was applied to an image. Then, the discrete Fourier transform (DFT) was applied to the low frequency subband of the DWT transform. Next, the phase information of the DFT was binarized to obtain the BPOF, which would be taken as the watermark and embedded into the corresponding magnitude. Compared to applying the DFT transform to the whole image and embedding the BPOF watermark in the entire frequency range, or in the low frequency range, the watermark robustness in JPEG compression is improved significantly while maintaining the watermark imperceptibility and detection efficiency. This method may be used to demonstrate the authenticity and integrity of an image. The simulation experiments demonstrate the efficiency of this method.     

Low cost measurement setup based on a piezoelectric microphone for estimating apple bruising using Shannon entropy

This study presents a low cost measurement setup for estimating apple bruise volume during drop impact tests. The proposed measurement system consists of three main stages namely recording impact sound, signal processing, and estimating bruise volume. In the recording stage, the impact sound occurred when striking the apple on the surface was recorded by a piezoelectric microphone into computer. The impact sound was converted into Shannon entropy signals based on the Kernel density approach, and two measurable quantities namely entropy peak and pulse-width time were extracted from Shannon entropy signals in the signal processing stage. In the bruise volume estimating stage, the regression curves that map entropy peak and pulse-width features into bruise volume are estimated using measurements data. To evaluate the performance of the proposed method, we conducted several drop experiments with six different drop heights and two different temperatures (1 and 19 °C). Experimental results showed that bruise volume was exponentially proportional to the entropy peak and it was inversely proportional to pulse-width time as power functions, and all the curves were fitted with coefficients of determination of more than 0.98. Moreover, it was found that colder apples developed less bruise volume then warmer ones.