保重心脉冲压缩滤波及其在速度自动拾取中的应用

To pick velocity automatically is not only helpful to improve the efficiency of seismic data process, but also to provide quickly the initial velocity for prestack depth migration. In this thesis, we use the Viterbi algorithm to do automatic picking, but the velocity picked usually is immoderate. By thorough study and analysis, we think that the Viterbi algorithm has the function to do quickly and effectually automatic picking, but the data provided for picking maybe not continuous on derivative of its curved surface, viz., the curved face on velocity spectrum is not slick. Therefore, the velocity picked may include irrational velocity information. To solve the problem above, we develop a new method to filter signal by performing nonlinear transformation of coordinate and filter of function. Here, we call it as Gravity Center Preserved Pulse Compressed Filter (GCPPCF). The main idea to perform the GCPPCF as follows: separating a curve, such as a pulse, to several subsection, calculating the gravity center (coordinate displacement), and then assign the value (density) on the subsection to gravity center. When gravity center departure away from center of its subsection, the value assigned to gravity center is smaller than the actual one, but non other than gravity center anastomoses fully with its subsection center, the assigned value equal to the actual one. By doing so, the curve shape under new coordinate breadthwise narrows down compare to its original one. It is a process of nonlinear transformation of coordinate, due to gravity center changing with the shape of subsection. Furthermore, the gravity function is filter one, because it is a cause of filtering that the value assigned from subsection center to gravity center is obtained by calculating its weight mean of subsetion function. In addition, the filter has the properties of the adaptive time delay changed filter, owing to the weight coefficient used for weight mean also changes with the shape of subsection. In this thesis, the Viterbi algorithm inducted, being applied to auto pick the stack velocity, makes the rule to integral the max velocity spectrum ("energy group") forward and to get the optimal solution in recursion backward. It is a convenient tool to pick automatically velocity. The GCPPCF above not only can be used to preserve the position of peak value and compress the velocity spectrum, but also can be used as adaptive time delay changed filter to smooth object curved line or curved face. We apply it to smooth variable of sequence observed to get a favourable source data ta provide for achieving the final exact resolution. If there is no the adaptive time delay-changed filter to perform optimization, we can't get a finer source data and also can't valid velocity information, moreover, if there is no the Viterbi algorithm to do shortcut searching, we can't pick velocity automatically. Accordingly, combination of both of algorithm is to make an effective method to do automatic picking. We apply the method of automatic picking velocity to do velocity analysis of the wavefield extrapolated. The results calculated show that the imaging effect of deep layer with the wavefield extrapolated was improved dominantly. The GCPPCF above has achieved a good effect in application. It not only can be used to optimize and smooth velocity spectrum, but also can be used to perform a correlated process for other type of signal. The method of automatic picking velocity developed in this thesis has obtained favorable result by applying it to calculate single model, complicated model (Marmousi model) and also the practical data. The results show that it not only has feasibility, but also practicability.

序列视觉信息整合的特性与机制

One of the great puzzles in the psychology of visual perception is that the visual world appears to be a coherent whole despite our viewing it through temporally discontinuous series of eye fixations. The investigators attempted to explain this puzzle from the perspective of sequential visual information integration. In recent years, investigators hypothesized that information maintained in the visual short-term memory (VSTM) could become visual mental images gradually during time delay in visual buffer and integrated with information perceived currently. Some elementary studies had been carried out to investigate the integration between VSTM and visual percepts, but further research is required to account for several questions on the spatial-temporal characteristics, information representation and mechanism of integrating sequential visual information. Based on the theory of similarity between visual mental image and visual perception, this research (including three studies) employed the temporal integration paradigm and empty cell localization task to further explore the spatial-temporal characteristics, information representation and mechanism of integrating sequential visual information (sequential arrays). The purpose of study 1 was to further explore the temporal characteristics of sequential visual information integration by examining the effects of encoding time of sequential stimuli on the integration of sequential visual information. The purpose of study 2 was to further explore the spatial characteristics of sequential visual information integration by investigating the effects of spatial characteristics change on the integration of sequential visual information. The purpose of study 3 was to explore the information representation of information maintained in the VSTM and integration mechanism in the process of integrating sequential visual information by employing the behavioral experiments and eye tracking technology. The results indicated that: (1) Sequential arrays could be integrated without strategic instruction. Increasing the duration of the first array could cause improvement in performance and increasing the duration of the second array could not improve the performance. Temporal correlation model was not fit to explain the sequential array integration under long-ISI conditions. (2) Stimuli complexity influenced not only the overall performance of sequential arrays but also the values of ISI at asymptotic level of performance. Sequential arrays still could be integrated when the spatial characteristics of sequential arrays changed. During ISI, constructing and manipulating of visual mental image of array 1 were two separate processing phases. (3) During integrating sequential arrays, people represented the pattern constituted by the objects' image maintained in the VSTM and the topological characteristics of the objects' image had some impact on fixation location. The image-perception integration hypothesis was supported when the number of dots in array 1 was less than empty cells, and the convert-and-compare hypothesis was supported when the number of the dot in array 1 was equal to or more than empty cells. These findings not only contribute to make people understand the process of sequential visual information integration better, but also have significant practical application in the design of visual interface.

Suppressing chaos and transient in parameter perturbed systems

The systems with some system parameters perturbed are investigated. These systems might exist in nature or be obtained by perturbation or truncation theory. Chaos might be suppressed or induced. Some of these dynamical systems exhibit extraordinary long transients, which makes the temporal structure seem sensitively dependent on initial conditions in finite observation time interval.

Determining of the delay time for a heating ventilating and air-conditioning plant using two weighted neural network approach

This paper presents an two weighted neural network approach to determine the delay time for a heating, ventilating and air-conditioning (HVAC) plan to respond to control actions. The two weighted neural network is a fully connected four-layer network. An acceleration technique was used to improve the General Delta Rule for the learning process. Experimental data for heating and cooling modes were used with both the two weighted neural network and a traditional mathematical method to determine the delay time. The results show that two weighted neural networks can be used effectively determining the delay time for AVAC systems.

Determining of the delay time for a heating ventilating and air-conditioning plant using multi-weights neurons approach

This paper presents an multi weights neurons approach to determine the delay time for a Heating ventilating and air-conditioning (HVAC) plan to respond to control actions. The multi weights neurons is a fully connected four-layer network. An acceleration technique was used to improve the general delta rule for the learning process. Experimental data for heating and cooling modes were used with both the multi weights neurons and a traditional mathematical method to determine the delay time. The results show that multi weights neurons can be used effectively determining the delay time for HVAC systems.

Identification of nonlinear dynamic systems: Time-frequency filtering and skeleton curves

The nonlinear behavior varying with the instantaneous response was analyzed through the joint time-frequency analysis method for a class of S. D. O. F nonlinear system. A masking operator an definite regions is defined and two theorems are presented. Based on these, the nonlinear system is modeled with a special time-varying linear one, called the generalized skeleton linear system (GSLS). The frequency skeleton curve and the damping skeleton curve are defined to describe the main feature of the non-linearity as well. Moreover, an identification method is proposed through the skeleton curves and the time-frequency filtering technique.

Identification of Nonlinear Systems Through Time-Frequency Filtering Technique

In the previous paper, a class of nonlinear system is mapped to a so-called skeleton linear model (SLM) based on the joint time-frequency analysis method. Behavior of the nonlinear system may be indicated quantitatively by the variance of the coefficients of SLM versus its response. Using this model we propose an identification method for nonlinear systems based on nonstationary vibration data in this paper. The key technique in the identification procedure is a time-frequency filtering method by which solution of the SLM is extracted from the response data of the corresponding nonlinear system. Two time-frequency filtering methods are discussed here. One is based on the quadratic time-frequency distribution and its inverse transform, the other is based on the quadratic time-frequency distribution and the wavelet transform. Both numerical examples and an experimental application are given to illustrate the validity of the technique.

Time-Frequency Analysis of Nonlinear Systems: The Skeleton Linear Model and the Skeleton Curves

The joint time-frequency analysis method is adopted to study the nonlinear behavior varying with the instantaneous response for a class of S.D.O.F nonlinear system. A time-frequency masking operator, together with the conception of effective time-frequency region of the asymptotic signal are defined here. Based on these mathematical foundations, a so-called skeleton linear model (SLM) is constructed which has similar nonlinear characteristics with the nonlinear system. Two skeleton curves are deduced which can indicate the stiffness and damping in the nonlinear system. The relationship between the SLM and the nonlinear system, both parameters and solutions, is clarified. Based on this work a new identification technique of nonlinear systems using the nonstationary vibration data will be proposed through time-frequency filtering technique and wavelet transform in the following paper.

Shock tube study of JP-10 ignition delay time

JP-10 (exo-tetrahydrodicyclopentadiene, C10H16) ignition delay times were measured in a preheated shock tube. The vapor pressures of the JP-10 were measured directly by using a high-precision vacuum gauge, to remedy the difficulty in determining the gaseous concentrations of heavy hydrocarbon fuel arising from the adsorption on the wall in shock tube experiments. The whole variation of pressure and emission of the OH or CH radicals were observed in the ignition process by a pressure transducer and a photomultiplier with a monochromator. The emission of the OH or CH radicals was used to identify the time to ignition. Experiments were performed over the pressure range of 151-556 kPa, temperature range of 1000-2100 K, fuel concentrations of 0.1%-0.55% mole fraction, and stoichiometric ratios of 0.25, 0.5, 1.0 and 2.0. The experimental results show that for the lower and higher temperature ranges, there are different dependency relationships of the ignition time on the temperature and the concentrations of JP-10 and oxygen.

Direct dynamical test for deterministic chaos and optimal embedding of a chaotic time-series

We propose here a local exponential divergence plot which is capable of providing an alternative means of characterizing a complex time series. The suggested plot defines a time-dependent exponent and a ''plus'' exponent. Based on their changes with the embedding dimension and delay time, a criterion for estimating simultaneously the minimal acceptable embedding dimension, the proper delay time, and the largest Lyapunov exponent has been obtained. When redefining the time-dependent exponent LAMBDA(k) curves on a series of shells, we have found that whether a linear envelope to the LAMBDA(k) curves exists can serve as a direct dynamical method of distinguishing chaos from noise.

Pipeline Architecture and Parallel Computation-Based Real-Time Stereovision Tracking System for Surgical Navigation

This paper studies the development of a real-time stereovision system to track multiple infrared markers attached to a surgical instrument. Multiple stages of pipeline in field-programmable gate array (FPGA) are developed to recognize the targets in both left and right image planes and to give each target a unique label. The pipeline architecture includes a smoothing filter, an adaptive threshold module, a connected component labeling operation, and a centroid extraction process. A parallel distortion correction method is proposed and implemented in a dual-core DSP. A suitable kinematic model is established for the moving targets, and a novel set of parallel and interactive computation mechanisms is proposed to position and track the targets, which are carried out by a cross-computation method in a dual-core DSP. The proposed tracking system can track the 3-D coordinate, velocity, and acceleration of four infrared markers with a delay of 9.18 ms. Furthermore, it is capable of tracking a maximum of 110 infrared markers without frame dropping at a frame rate of 60 f/s. The accuracy of the proposed system can reach the scale of 0.37 mm RMS along the x- and y-directions and 0.45 mm RMS along the depth direction (the depth is from 0.8 to 0.45 m). The performance of the proposed system can meet the requirements of applications such as surgical navigation, which needs high real time and accuracy capability.

MEASUREMENT AND SIMULATION OF THE TURN-ON DELAY TIME JITTER IN GAIN-SWITCHED SEMICONDUCTOR-LASERS

The turn-on delay time jitter of four different unbiased gain-switched laser types is determined by measuring the temporal probability distribution of the leading edge of the emitted optical pulse. One single-mode 1.5-mu-m distributed feed-back laser and three multimode Fabry-Perot lasers emitting at 750 nm and 1.3-mu-m are investigated. The jitter is found to decrease for all lasers with increasing injection current. For multimode lasers it decreases from 8 ps excited slightly above threshold down to below 2 ps at three times the threshold current. The jitter of the distributed feedback (DFB) laser is a factor of 3-5 larger than the jitter of the three multimode lasers. A new model to predict the turn-on delay time jitter is presented and explains the experiments quantitatively.