To develop a forward-looking and modulasized simulation platform for the concept study of the hybrid electric vehicle(HEV), taking a certain hybrid electric bus as example, a full model was built on the forward-looking software CRUISE, and a parallel control strategy was modeled for the whole vehicle in the environment of MATLAB/SIMULINK. The simulation results proved the credibility, the reliability and the multifunctionalness of the developed simulation platform. It makes sense for realization of platformness of the HEV development tool to enhance the concept study efficiency, shorten the development cycle, and reduce the decelopment cost.

According to the requirements of the electric bus on the electric power steering(EPS), a recirculating ball type EPS system was designed and its dynamic model was established.Because of the existence of system uncertainties in modeling, signal disturbance,sensor noise, considering the requirements on the system robustness and the dynamic performance, a mixed H2/H∞ controller was designed and optimized by the mixed weighted index optimization.The simulation results showed that this optimal control method could attenuate the random road excitation,torque sensor measurement noises and disturbances, reduce oscillations that might occur in the steering column,provide satisfied road feeling for drivers.The simulation results were verified by the bench test.The test results showed that the mixed H2/H∞ controller for the recirculating balltype EPS system is feasible and effective,and it improves the vehicle steering and handling stability.

The exterior noise of a truck was analyzed and predicted with the nearfield acoustic holography(NAH) and the space transformation of sound field(STSF). A measurement system of the NAH was built, a software of the STSF was developed, and they were used to measure and analyze the exterior noise source of the truck. The farfield noise characteristics and the maximal noise outside the accelerating truck were analyzed and predicted. The predicted farfield noise was validated by experiments, and the reasons causing error in acceleration noise prediction were discussed. The results showed that based on the nearfield holographic face measurement data, the sound field of the farfield arbilrary reconstruction face can be predicted with the STSF, the main noise source to form the planar sound field in that face can be identified, and the exterior maximal vehicle acceleration noise can be approximately predicted.

A rib equivalence model was proposed based on the equavalence theory of the bas element stiffness. Through a contrast analysis between the equivalence model and the traditional detailed model, the accuracy of the equivalence model was improved. A group of experiments was designed and performed to validate the equivalence model. The result provides a reference for the improving the accuracy and the effectiveness of CAE in the car body concept disign phase.

Using the element strain energy density theory, combining with the real body-in-white(BIW) structure, a structure modification method based on the relative sensitivity,i.e., the ratio of the strain energy density to the mass sensitivity, was proposed. In accordance with a finite element model of a BIW, the relative sensitivities of the all thinwalled components of the BIW were calculated and the results were compared each other. The components with higher relative sensitivities need to increase their thickness, otherwise to decrease it, to achieve the structure with high stiffness and light weight. There modification schemes to achieve different targets were presented from the analysis based on the relative sensitivity:high stiffness scheme, light weight scheme, and tradeoff scheme. The comparison on the results of stalic sliffness calculation showed that the tradeoff scheme leads to a satisfactory modification results, is the best BIW structure model to neet the design requirements.

The feasibility of using the dielectric constant as an evaluation index to evaluate the quality degradation of the lubrication oil was verified through theoretical analysis and experimental approach. A glasstube sensor to detect accurately the dielectric constant of the lubrication oil and a related PWM oscillation delection circuit were developed. A monitoring system to monitor online the comprehensive properties of the lubrication oil was made up based on the abovementioned components, thus realizing to change the vehicle lubrication oil according to its quality instead of according to visual obserration or on schedule.

The reentrant combustion chamber shape of a high-speed direct-injection vehicle diesel engine was improved to form required airflow-characteristics in the chamber. The dynamics of incylinder flow field, the airfuel ratio distribution, and the temperature field were simulated by commercial CFD software FIRE for the airflow matching the fuel spray characteristics by different injection pressures. The air-fuel mixture formation of the diesel engine was studied by simulation, and the effects of the obtained mixture formation behavior on the combustion and exhaust emissions were investigated experimentally. The results showed that the ignition delay, the premixed combustion proportion and the diffusion combustion process can be controlled by optimal matching between the airflow characteristics in the reentrant combustion chamber and the fuel injection pressure, thus to control the high temperature combustion duration. The optimization can effectively reduce the NOx and soot emissions simultanceously withoult penalty on fuel economy.

A numerical simulation of the thermodynamic cycle and especially the combustion process was performed for a turbocharged vehicle diesel engine using different multiple-injection strategy under high load by means of a 3-dimensional CFD numerical analysis software FIRE. The effects of injection timing of the single-injection, the pilot injection quantity and the interval between the pilot and the main injections of the dual-injection, and the two pilot-injections on the combustion process and the formation of NOx and soot were discussed. The simulated results indicated that better trade-off between the formations of NOx  and soot can be achcived by using the multiple-injection strategy than using the simgle-injection strategy. Under the single-pilot dualinjection strategy, increasing the pilot injection quantity and the interval between the injections leads to decrease of soot formation and increase of NOx  formation. The two pilot-injection strategy seems more effective in reducing the soot formation than the single pilot-injection under the same total pilot-injection quantity without obvious penalty on NOx  formation.

A study was performed to estimate the real-time vehicle queue length before the stop line at the urban signal controlled intersection. The relationship among traffic flow directions in road sections was analyzed, and two models,i.e., an artificial neural network model and a Bayesian network model were established to deal with the effects of traffic flows in the road sections, and the structure of the models was specified. To facilitate the practical application of these models, the principal component analysis was used to decrease the input dimensions, the EM algorithm and GMM were used to represent the parameters of the train models. A simulation road network was designed based on the real world data to validate the proposed models under various experiment scenarios. Simulation results showed that the Bayesian network model can grasp the traffic flow tendencies better than the artificial neural network model because of the randomness in the urban road network.

Based on the surveyed data,the arrival behavior of the exiting passengers and the relationship between the pedestrian flow and the density in the passage and at the stariway have been analyzed. According to the regressed flow-density curve, the queuing mechanism of the passenger at the exit stairway was studied when the passage has the two different widths relative to the stairway. It was showed that the horizontal speed  of the passenger at stairway is approximately equal to that in the passage wheu the jam occurs, but the passenger density at the stairway is lower tham that in the passage. The capacity of the stairway is lower than that of the passage, thus the queue occurs.

The cost and income of the feeder bus system of the rail transit were analyzed in consideration of the elasticity of the passenger demand for the headway and the fare of the feeder bus, and a nonlinear programming model as well as its solution method was proposed taking the maximization of the gross system profit as the target function and the passenger volume share of the rail transit as the constraint conditions. The numerical case study and the parametric sensitivity analysis showed, there is a local optimingation solution of the model in the frame of constraint conditions. The gross system profit gradually decreases in various rates with the increase of the average single passenger waiting time and the bus fare. The sensitivity of the passenger to the increase or decrease of the fare is more strong than that of the headway.

To deal with the elastic intercity travel demand of the passenger, the optimization of the compined decisionmaking involving the bus operating frequency and the ticket price of the passenger transport enterprise was studied. Comprehensively considering the passenger travel time adjustment cost, inbus congestion cost, travel ticket cost, as well as the fied cost, variable cost, and the allocated cost of the road construction and maintenance, an optimization model to maximize the total income of the passengers and the enterprise was established and its solving method was proposed.As an example, the travel time adjustment cost function of a special group of passengers was discussed in detail and numerically analyzed. The suggested optimization provides a theoretical foundation for the combined decisionmaking on the bus operating frequency and the ticket price.

The comprehensive transportation corridor(CTC) is the backbone of the regional traffic and transportation system. In the paper the combined capaeity of CTC was defined and a fuzzy optimization model of the multiobjective decisionmaking for the CTC combined capacity was proposed. Taking the transportation efficiency, transportation quality and the service level as 3 optimization targets, defining the 7 specific evaluation indexes, 3 feasible schemes were obtained by Trans CAD software, and evaluated by the proposed optimization model. The results provide a theoretical formdation and practical direction for the optimal allocation of the comprehensive transportation resources.

To analyze the bending resistance of the steel-concrete composite beam(CB) accurately, a new finite element stiffness equation of the CB in the structure under the vertical loads was derived based on the contact theory. The element considers the shear-slip effect between the shear connector parts located at the interface of the steel-concrete CB and simulates the displacement difference between the steel upper surface and the concrete lower surface by using two displacement modes in the interface. The calculated results were compared with the test results and good agreement showed the suggested method is reasonable and believable. Using the CB element, it is possible to calculate effectively the longitudinal distributions  of the bending deflection, the strain, and the sheer-slip strain difference in the interface of the CB under the vertical loads, to analyze the effect of the shear stud on the bending resistance of the CB. The suggested CB element can be extended to the calculation of the variable cross-section steel-concrete CB and the prestressed steel-concrete CB.

A theoretical model was established for the interaetion of the multiple-vehicle and bridge system using the D'Alembert principle and the hypothesis of Euler-Bernoulli beam. The motion equation of the vehicle-bridge system was decoupled by the model analysis method. The decoupled motion equation expressed in the matrix form of the generalized coordinates was solved by the eigenvibration theory to get the frequencies of the bridge loaded by vehicles. For the highway bridges with small or medium span, their vibrations were excited usually by a single vehicle, and the vehicle will stay on the bridge after excitation, so analytical expressions of the frequencies of the bridge under the action of a single vehicle were derived. The effects of the location of vehicle, the stiffness of its suspension spring, the mass above and under the spring on the difference between the loaded frequencies and the eigenfrequencies of the bridge were discussed.

The vehicle operations on the entrance and exit transition road section of the straight or curved tunnel were simulated by dynamics simulation means. The dynamic responces of the vehicle before and after the road pavement change were obtained. The effects of the vehicle acceleration, the braking intensity, the pavement material transition location, and the adhesion coefficient change on the vehicle operation were analyzed. The simulation results showed that the abrupt change of the adhesion coefficient at the pavement material transition is the primary contributory factor to vehicle accident a tunnel entrance and exit due to the yaw of the vehicle driving through the parement transition from the uneven trie loads on the left and right sides. The effect of the braking behavior on the vehicle driving stability at the entrance and exit of a curved tunnel is more significant than that of a straight tunnel, and the acceleration behavior shows even a more obvious effect. The transition location has a large effect on the vehicle driving stability. The tunnel design showed extend the road asphalt pavement at the entrance section to the location where the braking of vehicle has ended , and locate the exit transition before the vehicle starts acceleration. The adhesion coefficient of the concrete pavement inside the tunnel should be above 0.35 to avoid excessive difference of the adhesion coefficient.

Biological coupling elements are the main factors contributing to biological functions and the basic unit constructing biological coupling. Biological organisms can achieve a variety of biological functions efficiently by the combine of different coupling elements and coupling modes. Diversity of biological coupling elements and coupling mode exhibit inevitably diversity and complexity of biological coupling function. In this paper, the characteristics and types of biological coupling elements and the identification of the main and hypo-main coupling elements are analyzed, the coupling modes of biological coupling elements are revealed from the bionic viewpoint. Finally, the relations of the coupling elements, coupling modes and biological couplings are discussed.

The sand blasting erosion wear of samples with concave, flute and traffic circle bionic surface configurations was investigated by experiments. The optimal experimental design theory was employed and a three levels orthogonal table L27 (313) was adopted to arrange the experiments. Experimental data was processed by range analysis. The relationships between the erosion rate and the experimental factors, such as the rotation speed of sample, surface configuration, sand size (mesh) and blast rate, were obtained. The significances of the effects of these factors on the erosion rate are in the order: the sand mesh, rotation speed of sample, sand blast rate and surface configuration. The erosion rate increases with the rotation speed and sand mesh. Among all primary interactions, the effect of the interaction between configuration and sand blast rate on the erosion rate is the strongest one, while that between the sand mesh and rotation speed is the weakest one.

The response surface method based on the radial basis function neural nelwork(RBF-NN) was adopted to analyze the fatigue reliability of a loader boom.When the limit state function of structure is complex or highly nonlinear,it is time-consuming or cumbersome to carry out reliability analysis with traditional methods.The RBF-NNbased response surface method provides an effective means for the reliability analysis of the large scale structures.The working process of a loader machine was analyzed with the analytical approach combining the finite element method software ANSYS,the stress and strain histories of the loader boom were calculated by rainflow algorithm,consequently the fatigue life of the structure could be derived by the local stressstrain analysis.The RBF-NN based response method was used to fit the limit state function of the structure as well as its derivatives,so as to calculate the reliability of the structure.The examplified numerical results showed the proposed method is capable of solving the industrial-scale fatigue reliability problems.

A SIMPLEXT algorithm is established based on nonorthogonal collocated grids by using finite volume method. The algorithm explicitly treats the influences of adjacent velocity, source term and cross-derivatives on the velocity correction value. Detail of derivation of the algorithm is given, and numerical simulation of the inclined lid-driven square cavity flow is carried out. Results show that as Reynolds number increases the number of eddy increases, the inertia force also increases that enhances the flow inside the cavity. It is demonstrated that convergent solution can be obtained by the SIMPLEXT algorithm under relatively wide underrelaxation. The robustness of the algorithm is also better and it can be used for the calculation of flow fields with complex boundaries.

Taking full advantage of the multi-grid method to combine the processes of the grid discretion and the solution, the multi-grid method was applied to solving the structure dynamic response problem. A solving program by the multi-grid method was compiled, and the program was validated by calculation cases. Different multi-grid circulative algorithms were applied to calculate the dynamic response of the lamella, showing it was characterized by high precision,rapid convergence, and easy aceomplishment. The comparison by examples of different circulative algorithms indicated that the suggested N circulation algorithm is superior to the commonly used V and W circulations.

To deal with the complex nonlinear relation between the charateristic parameters and the flow regime of the gas-liquid 2phase flow, a flow regime identification method for this kind of flow was proposed based on the principal component analysis(PCA) of the wavelet packet and the least square support vector machine(LS-SVM).The 4-layer wavelet packet was decomposed for the acquired differential pressure fluctuation signal at 3 pressure measure intervals, and the characteristic vector matrix of the wavelet packet was formed. The input dimension of the characteristic vector matrix was reduced by the PCA. The dimension reduced vector matrix was applied to train identification of the LSSVM. The identification results showed that the principal component features fusing the informations from 3 sensors can identify the flow regine of the gasliquid 2phase flow more efficient than the condition of only one sensor.

To deal with such prblems in the hydrostatic transmission hybrid vehicle(HTHV) as large parameter perturbation and significant load change in vehicle starting and braking, the quantitative feedback theory was employed to shaping the transmission loop to get the robust stability, restrain the disturbance and enhance the tracking behavior. A robust controller with the friction torque compensation was designed to control the HTHV. Test results showed that the developed quantitative feedback robust controller is characterized by the good control result, effective attenuation of the parameter perturbation, the external disturbance and the effect of the intensive nonlineasity, improving the robust stability and the dynamic performance of the system.

A braking control strategy was proposed for a wheel drive hydraulic hybrid vehicle(WDHHV) based on the backward modeling method. The strategy considered the changes of the vertical loads, the braking safety, the braking energy regeneration efficiency, and the state of charge of the energy accumulator, to solve such key problems that influence the energysaving effects and the braking safety of the WDHHV as how to effectively utilize the energy saved by the regenerative braking, to reasonably distribute the regenerative braking force on each wheel, and to harmonize the relationship between the regenerative and the frictional braking. The relatiors among the vehicle speed, the pressure change in energy accumulator, and the regenerated energy were obtained through modeling and simulation in the environment of Matlab/Simulink. The results showed that the proposed strategy can effectively enhance the energy regeneration efficiency with the precondition of braking safety.

In order to enhance the output power of a piezoelectric generator(energy conversion system),power calculation models were established for the AC and DC-output circuits and their simulation analysis and test validation were performed.The analysis results showed that there were different optimal load resistances for the two output circuits to obtain maximal output power under a given open voltage of piezoelectric oscillator,which depends on its size and librating frequency.The optimal load and maximal power of the AC-output-circuit are 2/π and π/2 times those of the DC -output-circuit,respectively.The open voltage of the tested piezoelectric oscillator(58 mm×30 mm×0.7 mm) is 14.8 V at vibrating frequency of 44.3 Hz.Accordingly,the optimal analytical/tested load resistance of the AC and DC-circuits are 72/71 kΩ and 113/110 kΩ,and the maximal analytical/tested power are 0.76/87 mW and 0.49/4.7 mW,respectively.

FDTD (Finite Difference Time Domain method) is used to establish mathematical model and the radiation of the automotive mobile preparation system based on Bluetooth Technology is analysed on time domain and frequency domain for the electric dipole and Gaussian pulse. Two kinds of different frequency bands (150 K-30 M and 75 M-108 M) are analysed. The method and its circuits of ground drift and crosstalk suppression are designed. The simulation images have shown that it greatly suppressed the radiation of the mobile preparation systems. The intensity of electromagnetic radiation is reduced by an average 7.6 dB, thus it enhanced the electromagnetic compatibility of the mobile preparation system, also verified the effectiveness of two designs.

In order to obtain single malto oligosaccharide (maltohexaose, maltoheptaose, or maltooctaose),the ringopening reactions of α、β、γcyclodextrin were performed at 95 ℃ and pH 5.5 for 30 min using cyclomaltodextrinase.And,a novel method for the production of linear malto oligosaccharides from starch,hydrolyzed by cyclodextrin glucanotransferase and cyclomaltodextrinase, was proposed.

A high-order terminal sliding mode control method is proposed to solve non-minimum phase control problem and realize endposition control for two-link flexible manipulators. The method is based on genetic algorithm. The output of the manipulator system is redefined, and by input-output linearization, the system is decomposed into input-output subsystem and internal subsystem. To guarantee the stability of the two subsystems, a controller is designed by high-order sliding mode and terminal sliding mode for the input-output subsystem; and a genetic algorithm is adopted to optimize the parameters for the internal subsystem. The proposed method can weaken the influence of chattering on flexible modes and improve the precision of terminal controller. Simulation results are presented to validate the proposed method.

An equivalent jump system model of sampled-data control system is derived. Attention is focused on the design of an output feedback sampled data controller which guarantees the asymptotical stability of the closed loop system forall admissible parametric uncertainties. Sufficient conditions for the solvability of the stabilization problem are presented in terms of linear matrix inequalities and the parameter matrices of the desired output feedback sampled data controller can be constructed through feasible solution. Simulation of an aircraft shortperiod dynamic model is given to demonstrate the effectiveness and correctness of the proposed method.

The design requirement and mechanism of Lunar Rover with Center of Mass Varied (CMR-1) are briefly introduced. Based on the characteristics of wheelsoil interaction mechanics, the wheel sinkage, stability margin, motion resistance and drawbar pull of lunar rover in forward mothion are analyzed using terramechanics theory. From the mechanics analysis, the relationships between the configure parameters (such as the wheel parameters and the position of mass center) and the mobility performane indexes (such as the wheel sinkage, motion resistance and drawbar pull) are obtained. The design principles of the wheel parameters, position of mass center and the wheel space are given. It is demonstrated that the mass center is crucial to the mobility performance of the lunar rover. Simulation verifies that the CMR-1 is superior in obstaclesurmounting performance.

A piece wise linearized engine speed control model was built based on the idea of torque based engine control using the practical physical model and some of the engine runtime map data. The proposed model fully takes consideration of the external load disturbance and the saturation constraint of actuator. A robust moving horizon optimization control strategy with new performance optimization upper bound was proposed. It was applied to engine speed control, which can guarantee engine speed tracking, improve fuel economy and the ability of anti- disturbance. It is also capable to control the input air intake within the limit of the throttle. A commercial engine model EnDYNA was used to evaluate the performance of the controller. Simulation results show that the proposed controller can achieve desired performance.

In standard particle filter, proposal distribution is chosen without considering the most recent observation, so the variance of important weight increases with time, which results in weight degeneracy. To overcome this shortcoming, a new algorithm named the iterative sigma point filter is proposed. In the prediction stage, weighted particles are drawn from the probability density function by the sigmapoint filter. Then according to the observation data the weighted particles are updated. In the modification stage, iterative Kalman filter is adopted to optimize the mean and variance of the state distribution which are obtained in the prediction stage. Simulation of target tracking on reentry shows that this new algorithm can ensure the filter convergence. It also improves the estimation accuracy and robustness in comparison with the standard particle filter.

Focusing on the scheduling for observations of deep space spacecraft under uncertainty, the characteristics and background of deep space exploration mission are analyzed first. Then the uncertain factors of observations of deep space spacecraft are fully investigated. A hybrid scheduling strategy based on robust scheduling and dynamic rescheduling is proposed. Furthermore, the dynamic rescheduling unit is studied indepth. Details of the improved hybrid rescheduling strategy and the swarm intelligence based rescheduling method for observation rescheduling of deep space spacecraft are presented. Finally, a performance evaluation system based on time cost, efficiency and stability is established.

To express the topological relations between regions with holes, the elements of a 9-intersection matrix are extended to binary codes and a D9intersection model is proposed. The property of the D9-intersection model is investigated and its expressiveness is compared with the 9-intersection model. It is shown that the D9-intersection model can describe simple regional relations as accurately as the 9-intersection model can. The D9-intersection model can also distinguish the topological relations between regions with holes that the 9-intersection model can not. Its expressiveness outperforms the 9-intersection model. Its expression consists with human cognition well.

According to the concept of General Diagnostic Engine (GDE), an approach to identify minimal conflict sets is proposed. It is based on the Assumptionbased Trust Maintenance System (ATMS). By defining negativenode and new rules, the incompleteness of ATMS is overcome. The simplified entropy diagnostic measurement is realized using crude probability estimation; and a method based on simplified entropy using dynamic ε policy is put forward. Furthermore, details of dynamic update of candidate diagnoses after each measurement are given. This approach is incremental through propagating environments. It possesses the characteristics of correctness, completeness, consistency, all solution minimization and low diagnostic cost. Simulations also show that this approach is effective, general and easy to be implemented and expanded as well.

Traditional decision tree algorithms are sensitive to data distribution. The predictive accuracy of minority class is often decreased when the algorithm deals with skewed datasets. There exist some algorithms which can only handle the skewed datasets with only two kinds of classes. A new decision tree algorithm called DTID is proposed, which is insensitive to data distribution. Using this algorithm new cases of each minority class are generated to adjust the data distribution of the sample set, and the predictive accuracy of each minority class is improved. By adopting the modulus of each case previously, the running time of the algorithm is reduced. Experimental results show that, compared with C4.5 algorithm, the accuracy of DTID is obviously improved and it can obtain much better result even though there are many minority classes in the sample set.

A novel factorization of polynomial algorithm was proposed based on Gene Expression Programming (GEP). The fitness evaluation method for individual chromosome and the genetic operator of traditional GEP were improved. The difficulty in factorization of polynomial was analyzed. Then a novel factorization of polynomial algorithm based on gene reduction in GEP, FactorGEP, was proposed. In the proposed algorithm the number of valid genes in chromosome is taken as a factor in the fitness evaluation. Experimental results show that the FactorGEP algorithm can automatically perform factorization of polynomial well without any priori knowledge of the polynomial, and it can find the optimal factorization.

A trajectory clustering algorithm based on multidimensional Hausdorff distance is proposed for classification of trajectories of moving objects in intelligent visual surveillance system. First, the trajectory of a moving object is described using a sequence of flow vectors. Then the similarity between trajectories is measured by their respective multidimensional Hausdorff distances. Finally, the trajectories are clustered by the spectral clustering algorithm. The proposed algorithm is different from other schemes using Hausdorff distance that it includes both the position and direction information in the flow vectors; hence it can distinguish the trajectories in different directions. A distance preserving transformation is also proposed to reduce the computational complexity of the similarity measure. Experimental results show that, comparing with other algorithm, the clustering accuracy of the proposed algorithm is better, and the proposed distance preserving transformation can greatly reduce the computational cost.

To model the attention mechanism of human visual system, a visual attention model by fusing spatiotemporal features was proposed. The model is based on the bottomup computational framework, and it uses three low level visual features, including the luminance contrast, the texture complexity and the motion information of foreground objects. By fusing the spatial and temporal features, the visual saliency map of the scene can be achieved. Experimental results show that the proposed model can analyze the saliency of various regions in the sense effectively. Compared with Walther and You models, the proposed model can extract the focus of attention (FOA) in the scene more accurately.

We present a novel collision detection algorithm based on spherical blend skinning. A procedure is put forward for refitting of bounding spheres for spherical blend skinning with linear time complexity. Quaternion is used to construct the rotation bound. This refitting operation is an extension of the refitting for linear blending. Rotational component method is applied to complete the decomposition from spherical blending to linear blending. Experiment results show that using the proposed algorithm can quickly and efficiently achieve and process collision detection of objects in complex environment.

A computational model of event based on asynchronous dataflow (EADF) and its formal description are presented. This model has been independently implemented in dataflow visual programming language, LabScene2.0 which can develop virtual instruments. Simulation System of Nuclear Magnetic Resonance Instrument Searching for Water is taking an example to analyze and explain. DFVPL based on EADF has reduced the design of parallel for programmer and the performance has greatly improved in statically scheduled loop, great amount of computation and resource achieving in net or local system I/O.

The main reason for the matching performance degradation caused by the output transformer mounted on the ultrasonic generator was analyzed. Then, based on the theory of the aircore transformer model, a novel primary serial matching scheme for the piezoelectric ultrasonic transducer was developed. This scheme eliminates the traditional matching inductor mounted on the secondary coil. If the total load, which is composed of the output transformer and transducer, shows inductive impedance at the mechanical resonance frequency of the transducer, a serieswound suitable capacitor can achieve better performance than the traditional matching inductorbased scheme. Otherwise, a comportable serieswound inductor is needed. As a result of the above treatment, the state of conjugated matching between the supply amplifier and its load is reached. A series of texts demonstrate that, in comparison with the traditional secondary serial inductor matching scheme, the new scheme takes advantage in term of the matching precision and power transmission efficiency.

A model for the removal of multiplicative noises was proposed based on the non-local diffusion method. Under the assumption that the image is corrupted by Gaussian noise, the energy functional for image recovery was established and a partial differential equation was obtained by the calculus of variation. Experiments on synthetic image and realworld image were conducted. Results show that the denoising effect of the proposed model is better than that of the model based on bounded variation.

Rangebased localization schemes are sometimes not feasible due to hardware cost and resource restriction of sensor nodes. The geometric relationships and communication constraints among unknown node and anchor nodes are studied. A weighted centroid localization algorithm based on intersection of anchor circle is proposed. If there are anchor nodes within the communication range of an unknown node, the unknown node must be inside the triangle constituted by the intersection of the anchor circles. It is assumed that the location estimation of the unknown node is the triangle centroid. To increase the positioning accuracy an improved scheme is proposed. It uses RSSI as weight function and takes the weighted centroid of the triangle as the location estimation of the unknown node. This rangefree algorithm is based exclusively on connectivity of sensor networks. The communication and computational loads are small. Simulation results show that the relative localization error is 22.7% when 100 sensor nodes are randomly deployed in 100 m×100 m scenario with 30 m communication range, and the anchor density is 16%.

A lowcomplexity multiuser detection algorithm for Low Density Parity Check (LDPC) coded UltraWideband (UWB) systems is proposed. The algorithm applies the Turbo iterative method for multiuser detection. It combines soft interference cancellation and Minimum MeanSquared Error (MMSE) filter to significantly decreases the complexity of the receiver. Simulation results show that the proposed system outperforms conventional systems. With a few iterations the proposed system can effectively restrain multiaddress interference and its performance is close to that of a singleuser system.

This paper presents a new method for two-dimensional (2-D) directionofarrival (DOA) estimation of coherent signals with a special array. This method needs only two orthogonal linear arrays to estimate the 2-D DOA of different users. It uses one of the two linear arrays to pair the 1D DOA which is estimated by the two linear arrays respectively. It constructs a new covariance matrix based on the spatial smoothing method to further resolve the coherence between the two signals. The influence of the coefficient on the DOA estimation is analyzed. The proposed method is validated by computer simulation.

The difference of degree of nonlinearity between normal and epileptic electroencephalogram (EEG) signals was investigated by quantified delay vector variance (DVV) method. The quantified DVV method can be used to determine the degree of nonlinearity of the analyzed time series based on surrogate data. We compare the results of the degree of nonlinearity of EEG signals obtained by different surrogate data generation methods, namely Iterative Amplitude Adjusted Fourier Transformation (IAAFT) and Phase Randomization (PR). It is shown that there exists difference between the degrees of nonlinearity of the EEG signals obtained by the two surrogate data generation methods. However, results obtained by the two surrogate data generation methods show that both normal and epileptic signals are nonlinear, and the degree of nonlinearity of epileptic EEG signals is higher than that of normal EEG signals. Therefore, it is proposed that the difference of degree nonlinearity between normal and epileptic EEG signals can be used as the feature for the detection of epileptic seizure.

A packet decoding method for convolutional codes is proposed based on Field Programmable Gate Array (FPGA). It overcomes the shortcomings of larger consumption of hardware and lower decoding speed with the traditional Viterbi method. By this method the data to be decoded are divided into several groups first, and the mutual influences among the groups are fully considered. Then the data of different groups are decoded respectively. The final decoding output is obtained after integrative consideration of the decoding results of each data group. Investigation shows that, with the same feedback depth, the proposed decoding method can save hardware consumption and increase the decoding speed in comparison with the traditional Viterbi decoding method.

The performance of timehopping UltraWideband (UWB) system over IEEE 802.15.3a multipath channel model is analyzed. First, it is proved that the interference between a pulse and its own multipaths cannot be ignored; then a mathematical model is established to evaluate such interference. An exact expression of the average Signal to Interference plus Noise Ratio (SINR) is deduced, which shows that the SINR is determined by the selfcorrelation function between the channels' parameters and the pulse shape. It is shown that the exact expression is in good agreement with the simulation result. System performances using Gaussian pulse and optimal waveform designed with SDP algorithm are analyzed and compared. Results show that the optimal waveform is more sensitive to multipath interference, which results in worse performance with the same channel parameters.

A novel constant modulus blind equalization algorithm (CMA) with accelerated convergence is proposed. It is based on the concepts of setmembership and datareusing. Applying the idea of affine projection, the algorithm includes many constraint sets, whose number is equal to the length of datareusing. Compared with basic CMA, the convergence rate of the proposed algorithm is significantly faster; meanwhile, the excess mean square error can be maintained in a relatively low level because of the idea of setmembership. Deriving details of the algorithm are presented and its performance is analyzed theoretically. The convergence rate and stational error of the proposed algorithm are compared with those of other constant modulus algorithms by computer simulation.