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Deconvolution is a effective method of enhancing the bandwidth of seismic data, can improve vertical resolution of seismic data.
On the recovery of missing low and high frequency information from bandlimited reflectivity data.
Seismic Data Analysis: Processing, Inversion, and Interpretation of Seismic Data.
Further improvement of temporal resolution of seismic data by autoregressive (AR) spectral extrapolation.
Generalized linear inversion of reflection seismic data.

Data from the World Health Organization indicates that within developing nations, an estimated 40 million individuals have undergone amputation [26].
The analysis yielded critical data on material properties, including mass, volume, tensile strength, yield strength, density, and weight.
The initial stage of the data processing pipeline involves noise reduction.
EMG sensor signals are inherently susceptible to noise, making real-time user intention prediction challenging based on isolated data points.
The moving average filter is a fundamental low-pass Finite Impulse Response (FIR) filter commonly employed for smoothing sampled data or signals.

Based on a large number of carbon and oxygen stable isotope data, researched environment characteristics of Ordovician carbonate rocks in Yubei area, Tarim Basin.
According to carbon, oxygen stable isotopes (&13C, &18O) data, combining the diagenetic environment characteristics studied all kinds of geochemical characteristics of rocks in Yubei area.
Author used a lot of carbon and oxygen stable isotope data analyzed the geochemical characteristics and its environmental implications of the study area.
Sea-level changes control of burial rates of organic carbon, rise of the sea level corresponds to a greater burial rates of organic carbon, since the rising sea levels lead to a reduction in the ancient area of land and then the amount of organic carbon from land to ocean also decreased, which makes &13CPDB relative increase in inorganic carbonates[7].

In this paper, we use the well-known model proposed by [3] which has a linear decay and is given by (1) c determines the white phase noise floor of the oscillator. a gives the phase noise level near the center frequency up to . b is the steepness of noise reduction with increasing frequency distance up to where the noise floor becomes dominant.
The whole steps are shown below: Step1: Coarse data estimate 1) LS estimation at pilot subcarriers to obtain pilot frequency responses. 2) Linear interpolation at time domain between adjacent symbols. 3) Linear interpolation at frequency domain to get all frequency responses. 4) Coarse data estimation utilizes the frequency response coefficients.
Step2: ICI cancellation 1) Construct ICI channel matrix by Taylor’s expansion. 2) Substract the ICI coefficient of received data. 3) And then update the received data.
Step3: Fine data estimation and decision feedback 1) LS estimation and linear interpolation at both the frequency and time domain from the update received data to get ICI free data. 2) Using the decision feedback procedure with ICI free data, get the feedback data.
Step4: Update the phase noise vector by relation between feedback and received data of present time.

In this paper, the design of smart state machine and various data processing module.
Constantly from the frame, on the other hand, the cache to retrieve data, is in accordance with the prescribed format output.
The FPGA as the logic control chip, responsible for identifying the source signal, the image data according to certain format writing frame cache, while at a fixed rate of reading data from the frame buffer, and generate the corresponding sync signal, sent to the DAC together; Block and EEPROM used in active serial mode of the FPGA configuration on electricity.
The image processing system design based on FPGA Image processing system should be implemented based on FPGA and external to communicate with other systems, or receive the output image data, cache the image data, and meet the requirement of algorithm, and thus to hardware algorithm processing of images, and have certain ability of the advanced treatment of image.
After the completion of the system configuration, video acquisition device for video images, each frame by the analog-to-digital conversion generated image data into preprocessing module, after preprocessing the image data into SDRAM memory, the subsequent processing of the image by the Nios II processor and control, after processing of the image by digital to analog conversion on the monitor real-time display.

The data obtained from the experiment is shown in Table 1.
The diagram of curves Fig. 3 shows the relationship between the processing speed and roughness of workpiece surface refereed to the experiment data.
The data obtained from the experiment is shown in Table 2.
The diagram of curves Fig. 4 shows the relationship between the magnetic field intensity and roughness of workpiece surface refereed to the experiment data.
Conclusion The experimental data from Table 1 to Table 3 are measured by 80 orders for abrasive particle size.

According to the simulation experience and related data, the maximum number of iterations is 20, water content tolerance is 0.0001, pressure head tolerance is 0.1, upper optimal iterative range is 7, the lower optimal iterative range is 3, upper time step multiplication factor is 0.33, the lower time step multiplication factor is 1.3.
Water flow parameters.According to the Van Genvchten-Mualem model and software unique experience of soil parameters database, combined with the experimental measured data, set up the moisture migration parameters are shown in table 1.
In combination with the determination of the actual test data at the same time, compared with the simulation results, found the simulated data and experimental data have the same change trend, as shown in figure 1 ~ figure 3, the simulation accords with actual situation, software reliability is verified.
Fig.1 Ammonia nitrogen simulation data and test data comparison chart Fig.2 Nitrite-nitrogen simulation data and test data comparison chart Fig.3 Nitrate-nitrogen simulation data and test comparison chart Analysis.
Initial interactions with two autotrophic nitrification occurs under the action of bacterial nitrification, ammonia nitrogen under the action of nitrite bacteria is converted into nitrite-nitrogen, nitrite nitrogen under the action of nitrate bacteria is converted into nitrate-nitrogen, this will cause the reduction of ammonia nitrogen, nitrate on the rise.

The value of ϕj is estimated by fitting the AR model to the time history data.
The training data were composed of half of signal 1 and 2.
In order to compensate for the nonstationarity of the AR parameter sequence, the training data and testing data were taken alternately from the relevant feature sets.
Better diagnosis was obtained by employing multiple data sets than just by using each test data set separately.
Roeck: Structural Damage Identification Using Modal Data.

According to the results of measuring the wind speed site, binding studies of literature data, simulation and optimization of the impeller for fan, in order to determine the type of the selected impeller; analyzed by the mathematical model of the car to increase fuel consumption, this means economic results show generated is considerable.
For high-speed auto wake status quo power, this paper presents the design of a new wind power installations, and provide new ideas for the design of a vertical axis wind turbine, while enhancing people's awareness of energy conservation and emission reduction.
Select a series of discrete points within the study area were drag analysis, the data in Table 2: Table 2 Displacement and resistance difference Displacements/m Poor resistance ∆F/N Displacements/m Poor resistance ∆F/N 14 2.366 17 23.221 15 5.330 18 30.185 16 13.448 19 46.682 The resulting data into matlab to fit in, get ΔF s approximate relationship with ΔF = f (s),and s= v·t, so you can get:∆F =(1.973t4-4.666t3+4.131t2 – 0.619t + 0.2371)* 105 (N) Integration into the above equation was:∆Q= 1.1118*10-5 (L) About RMB 7.7824*10-5million, this time period generating capacity of 3.9 *10-5million.
First of all, the relationship between dynamic torque changes over time should be imported into Adams through Spline Spline linear data, then add friction and resistance moment, finally get the system output speed curve of change over time.

The DSP module was used for data analysis, and the results were displayed in the LCD module.
The PC signal processing software includes the functions of data communications, data display, data storage, analysis of algorithms, graphics, etc.
PC software design The PC Data processing software was programmed in VC + +6.0, and modular design structure was adopted.
Figure 3 PC software structure The communication settings module includes serial port settings, data reception, data transmission and data storage, to achieve data communication between the PC and the portable devices.
Analysis of gear noise and design for gear noise reduction.