In order to improve the electromagnetic compatibility of the dual-motor hybrid power-train system, the electromagnetic interference of the system power source was analyzed; then the FlexRay control network was developed base on V-mode development process. The optimization method, which combines signal segmentation and packaging, was employed in setting the length of the static segment slot. Semi-physical simulation was carried out on a platform with CANoe, FlexRay network interface and real nodes. Results show that, for hybrid vehicle, such systems with severe electromagnetic interference and high real-time requirement, FlexRay bus has more advantages than CAN bus.

Automatic transmission shift schedule with two parameters of the vehicle cannot adapt to the driver's intentions and change of driving conditions, and is unable to effectively use engine assisted braking in deceleration brake conditions. Based on the analysis of the necessity of engine assisted braking, a method of gear position decision is proposed, which is based on the fuzzy inference of braking duration, loads, braking deceleration, velocity. This method considers the driver's intentions and the external environment. Road tests indicate that the control strategy could adapt to the driver's intention and the external driving environment. The engine assisted braking can be used effectively. The control strategy improves driving safety of automatic transmission vehicle.

To evaluate the level of danger of current dynamic situation, a concept of collision avoidance time buffer, T_buffer, is proposed to calculate how much time buffer is left for driver or the control system to react. Based on T_buffer, a graded collision warning/avoidance algorithm is designed to adjust to different driving behaviors. Through audio/visual warning and active braking intervention, effective collision avoidance action can be realized. Simulations were carried out to compare the proposed algorithm with other four algorithms under three conditions. Results show that the proposed strategy is not only in accordance with driver's collision avoidance reaction, but also improves vehicle active safety effectively.

The basic structure and working principle of the semi-active hydraulic mount is introduced. According to the mechanical model, the mathematic model is built; then a semi-active hydraulic mount model containing the mechanical parts and fluid is built. Each inner structures, the motion situation of the fluid and gas, the open and close of the air channel are all considered in the model. In order to get accurate model parameters, a test is conducted to identify the parameters, such as the equivalent pumping area, the rubber volumetric stiffness, the membrane volumetric stiffness and the decoupler stiffness. The model is simulated using the identified parameters. The dynamic stiffness and loss angle obtained from the simulation are compared with that of experiment. The comparison results demonstrate the reasonability and the accuracy of the parameter identification method and the mount model. The semi-active hydraulic mount model could provide a foundation for the mount structure optimization and full vehicle modeling.

Front pendulum impact test of flathead heavy commercial vehicle has potential of the losses of occupant survival space and structural integrity of the suspension and other connections. To overcome such problems, dynamic models of ECE R29-03 (European prevailing commercial vehicle passive safety regulation) front pendulum impact test was established. A new front suspension bracket and an energy absorber structure were designed based on the analysis of the load transmission path during collision process. The effectiveness of the new front suspension bracket and the energy absorber structure was verified in the ECE R29-03 front pendulum impact virtual test. This research provides the basis for improving passive safety of heavy flathead commercial vehicles.

A new mechanism connecting seat cushion frame and seat back frame of automobile is designed using the instantaneous center principle of four bar linkage mechanism. The important design parameters, such as notch angle, notch clearance, notch curvature and friction coefficient are optimized using Finite Element Analysis (FEA) method. The feasibility of the mew mechanism is verified through rear-end collision test.

To investigate the evaluating accuracy of Quasi-static (QS) method and the analysis correctness of tank vehicle rollover stability, the relationship between the actual transient liquid sloshing effects in partially-filled oval tanks and the QS evaluating results are studied. Then, the impact of transient liquid sloshing on vehicle rollover stability is investigated by analyzing the balance between the rollover moment caused by the movement of the center of gravity of liquid bulk and the aligning torque caused by the load transfer between tires of the two sides. Finally, the key points that influence the intensity of transient liquid sloshing and the optimal tank shapes are discussed based on the rollover stability analysis results of tank vehicles with different oval tanks.

To overcome the shortcoming that the existing route guidance algorithms can not execute sequenced route search, a new Artificial Searching Swarm Algorithm (ASSA) is developed that can query multi-Point of Interests (POIs) in travel processing. The ASSA can optimize search topological structure of the road-network, which greatly reduces the amount of data access. Thus the optimal path can be presented according to the spatial-time correlation reasoning. Further more, the POI data are categorized based on urban POIs and a method to go through the sequenced POIs under multi-rules is developed. Sensitive experiments were implemented to verify the proposed ASSA. Results show that, compared with NS algorithm, ASSA can improve the computing efficiency by at least 16%, and it can also avoid getting less-than-optimal path. It effectively meets the travelers' sequenced travel demand.

Image processing technology was used to extract the basic data of pedestrian-vehicle conflict. Time Difference to Collision (TDTC) and the vehicle speed were selected as the features for pedestrian-vehicle conflict analysis. Based on the analysis, the corresponding membership functions of the two features are constructed to distinguish the safety level of the conflict. The proposed method is compared with of artificial discrimination. Results demonstrate that the proposed method is reliable and has good performance. The discriminating accuracy of the method is higher than 85%.

Through driving simulator experiments, the original performance data of different drivers on different road lines were collected, from which the characteristic parameters were extracted using statistical analysis. Then cognitive distraction detection models were developed based on the support vector machine in view of different road lines. The characteristic parameters were used as the input of the models. The experiment results show that, using the proposed models, the detection accuracy is 88.58% for straight road, and 81.25% for curve road. The performance of the proposed models is better than that of the universal model, using which the detection accuracy is only 74.17%. Experiment results also show that the cognitive distraction detection is also influenced by the driving styles of the individual drivers.

First, the new information was defined and its change was online monitored. The mean and variance of new information were input into the fuzzy controller. Then, the fuzzy logic was used to adjust the importance weights of system noise and observation noise. The new method overcomes the shortcomings of traditional filter, which can not real-time track the change of environment. It adapts to the dynamic change of traffic state to realize the optimization estimation. The method was tested on urban expressway in Guangzhou using real-time detection data. The results show that the proposed method has better tracking ability than traditional Kalman filter. There was a slight difference between the prediction result and that of actual observation in free traffic flow state and stable flow, and the relative error was under 10% in congested traffic state.

Two-dimensional boundary coordinates of 99 irregular aggregates were extracted after digital processing of asphalt concrete CT images. The modified Fast Fourier Transformation method (FFT) was used to obtain the fitting functions of those coordinates and the irregular particle form database was established. With the established database and PFC^2D software, a program for two-dimensional virtual mechanical simulation of asphalt concrete with irregular particles was written. Taking three gradations as an example, under the same void, virtual simulations of Double punch test and Split test were carried out. The test results show that the presented method can automatically generate digital specimen and the generated digital specimen can satisfy the requirements of micro mechanical properties numerical analysis of asphalt concrete.

The mechanical characteristic of the soft dredger fill, which is stabilized by the CJDS07 agent, is studied in Tianjin new area. The results show that the compression modulus, shear strength and structure of the stabilized soft dredger fill increase with the curing age. The stabilized soil gradually changes from high compressibility to middle compressibility. The stress and strain relationship of the stabilized soil is highly influenced by the confining pressure, that when the confining pressure is smaller than a certain value, the relationship is tend to be strain softening, otherwise, it is strain hardening. Based on the above research results and Dun-Chang model, the stress-strain relationship model suitable for the stabilized dredger fill is established.

To enhance the Swirl intensity of the diesel engine with semi-open combustion chamber, bionic non-smooth elements of pit, convexity, U-shaped groove and V-shaped grooves are used on the inside surface of diesel helical intake port. CFD numerical simulation of the flow in the diesel helical intake port with bionic non-smooth surface was conducted using CATIA, Hypermesh and Fluent. The Flow Coefficient and Swirl Ratio on non-smooth surface with four elements and on smooth surface were compared. It is shown that with little change in the Flow Coefficient, the Swirl Intensity is significantly enhanced by the non-smooth surface.

The dynamic load strength of over-running clutch of dual-turbine torque converter of a loader was analyzed. First, according to the engine speed and the speed ratio of the torque converter under 12 states in one working cycle, the speeds of I-turbine and II-turbine of the torque converter in each state were calculated. Second, based on the speeds, the torques of I-turbine and II-turbine in each state were calculated in CFD. Thus the stress of the roller, inner ring and outer ring of the over-running clutch in different period of time was calculated. Third, the over-running clutch was dynamically analyzed using finite element method, and the instantaneous stress distribution maps of the roller, inner ring and outer ring of the over-running clutch were obtained. Finally, the maximum stress position was given. This study provides a theoretical basis for the structural optimization of over-running clutch.

The hydraulic braking characteristic of traveling motor for excavator with a balance valve was improved by analyses of main parameters based on the braking system model. The main parameters, such as conical degree of main poppet, diameter of orifice, volume of sensitive chamber, spring stiffness and mass of valve core, were investigated. Theoretical analysis and experiment results of the hydraulic braking characteristic of the motor show that reducing the diameter of orifice and reducing the spring stiffness are beneficial to prolong motor hydraulic braking time. The results also show that the practical hydraulic braking time of the motor is 0.8s and the motor braking pressure is 1.2MPa. The experiment results are in agreement with that of theoretical analysis.

A reliability growth prediction model is established based on Weibull distribution. Considering factors influencing the reliability of the punching machines, the factor weights are determined by fuzzy scoring and analytical hierarchy process. The punching machine is partitioned into six serial subsystems. Comparing the reliability status of every subsystem, reliability growth coefficient is proposed based on reliability influencing factor weight and fuzzy scoring. Reliability prediction model is established by combining reliability growth effective coefficient and the Monte Carlo simulation. The model can be used to predict the reliability index. Comparison of the predicted reliability and the actual reliability index indicates that the proposed method is practicable.

A correction model of aligning large-scale machine set to its center is proposed. The model is based on bionic imaging theory with photoelectric multipoint. A numerical partial-differentiation equation set is established based on iterative algorithm to determine the optimal adjustment of the bearing shell. The proposed model can detect and align large-scale machine set to its center. This correction model is verified by simulation experiments.

The penetration mechanism of the mandibular stylet of cicada with non-smooth shape is analyzed. A bionic needle with saw tooth, which is inspired by cicada stylet is designed. The binary quadratic regression and orthogonal combination test optimization design method are employed to research the influences of two bionic structural parameters, the width of serrate and the interval of serrate, on the puncture resistance of syringe needle. A regression equation of the cicada stylet is obtained. The structure parameters of the optimal bionic saw tooth needle are that the width of serrate is 0.3 mm and the interval of serrate is 2.5 mm, and its drag reduction rate is 43.21%. The drag reduction effect of the saw tooth bionic needles is attributed to the decreasing contact area, forming rolling bearing model and producing microseism. This study provides the basis for the development of bionic painless needles.

The principle and characteristics of flexible rolling and stretch forming technology was proposed. A finite element model of spherical parts was built by explicit dynamic analysis. The effects of the thickness, width and properties of the material on the forming quality were discussed. The results indicate that under the condition of the same press displacement of the flexible roller, the compression and tension deformations of the sheets' inner and outer layers are enlarged with the increase in sheet thickness, which makes the plastic strain region increase and the springback decrease. When the width of the sheet increases, the mobility decreases on the middle, and the distribution of plastic deformation becomes inhomogeneous. Compared with 08AL, the equivalent plastic strain value of 2024 aluminum plate is bigger and the springback is smaller. The feasibility and practicability of this technology were proved by tests on an experiment machine, and the simulation results are useful for the practical rolling forming process implementation of sheet metal.

Tungsten Inert Gas (TIG) welding technology was employed to study the weldability of THQ50-C filler metal of 4 mm sheet thickness 22MnB5 after hot stamping. The microstructures and mechanical properties of the welding joints under different welding parameters were analyzed. Results show that, under the condition of DC-TIG welding, welding defects were found when the welding current is 60 A and 100 A; at 80 A welding current no macroscopical were found on the test pieces, but widmanstatten structure appeared in weld metal. While the DC pulse TIG welding was applied, high quality joint was available when the average welding current was only 60 A. The weld metal, coarse and fine grain zones of Heat Affected Zone (HAZ) were all composed of ferrite and pearlite; lath martensite, lower bainite and pearlite distributed in high temperature tempering zone of HAZ; granular carbide was separated out from the lath martensite in low temperature tempering zone of HAZ. Microhardness of the test pieces increased with the distance from the weld center, but the tensile strength was 631 MPa, about 42.1% of that of base material.

The surface of 3Cr13 martensitic stainless steel was irradiated by High Current Pulsed Electron Beam (HCPEB). The microstructures of specimens before and after irradiation were characterized in detail using XRD, SEM and TEM. The mechanical property and corrosion resistance of irradiated samples were examined. It was observed that, after HCPEB irradiation, a melting layer with depth of about 4 μm was formed on the surface. Further microstructural investigations indicate that the surface melted layer consists of nanocrystalline austenite and fine carbide particles, which primarily appear at grain boundary triple junction. The microhardness of the irradiated surface was increased significantly. The electrochemical corrosion resistance of the irradiated surfaces was also improved obviously. The formation of the nanocrystalline austenite layer induced by HCPEB was believed to be the dominating reason for the improvement of comprehensive performance of the material surface.

A design method of decoupling adaptive sliding mode controller unsing integrated factor is proposed for trajectory tracking and stabilization control of the Ball and Plate System (BPS). In this approach, the nonlinear system is decomposed to four subsystems and the state response of each subsystem is designed by a corresponding sliding surface. In the design, the integrated factor is adopted to combine the sliding surface, which is decided by an adaptive fuzzy algorithm based on the Lyapunov stability theory. Thus the stability of the system is guaranteed and the complex calculation is avoided. The proposed design method is applied to investigate Ball and Plate Vision System. The simulation results demonstrate that the proposed approach is effective in resolving the stabilization control and trajectory tracking control tasks of nonlinear and under-actuated system with uncertain terms.

A variable sampling period Modified Volterra model is proposed for the Air-Fuel Ratio (AFR) control system in Spark Ignition (SI) engine. On this basis, a joint Nonlinear Model Predictive Control (NMPC) method is developed based on the Radial Basis Function Neural Network (RBFNN) model combining with the modified Volterra model. The advantages of this method are small amount of calculation and high prediction accuracy; also the optimal control sequence can be directly calculated. Thus it significantly improves the AFR control performance of SI engine, and greatly reduces the computing time compared with the conventional iterative optimization algorithm. Real-time simulations based on the mean value engine model are conducted on the dSPASCE simulation platform. Results show that the control performance of the proposed method is significantly better than the RBFNN model or the Modified Volterra model based NMPC method.

First, the singularity problem is analyzed in the conventional fast terminal sliding mode controller when applied to six-axe harmonious motion control of the 6-DOF manipulator. Then, a non-singular fast terminal sliding mode controller is proposed, and the stability of the control system is proved using the Lyapunov theory. The non-singular fast terminal sliding mode controller is applied to six-axe harmonious motion control of the 6-DOF manipulator. The results illustrate that the non-singular fast terminal sliding mode method can improve the stability, accuracy, convergence speed and robustness of the position and orientation control of 6-DOF manipulator.

A trajectory tracking method is proposed for three-order uncertain nonholonomic mobile robot with actuator dynamic model. This method is based on the backstepping technique and dual reinforcement learning adaptive fuzzy logic system. The shunting control technique is used to prevent the velocity jump at the beginning of system for the motion controller. The reinforcement learning adaptive fuzzy logic control is employed for both body dynamics and actuator dynamics, such that the unknown system uncertainties of parameters and non-parameters can be compensated optimally. Moreover, in order to enhance the control performance, the robust compensators are applied to eliminate the impact of unknown external disturbance and approximation error of fuzzy system. The stability and ultimately bounded convergence of the control system are proven by Lyapunov theory. The validity of this method is verified by the simulation results.

The hydraulic actuated motion system of a biped robot, which has 8 degrees of freedom, with payload capacity is proposed. Comparing with the motor driving robots with the same payload capacity, the robot developed in this research has the advantages of smaller volume and better dynamic characteristics. For that the primary mass is concentrated on the legs when the robot is idle load, a dynamic balance control method in the coronal plane is proposed. Unlike the inverted pendulum model, this control method has no constraint on the mass distribution of the biped robot, which enlarged the application range. The effectiveness of this hydraulic actuated motion system of the biped robot is demonstrated by simulation experiment on Automatic Dynamic Analysis of Mechanical System (ADAMS) and physical prototype idle load experiments.

First, the motion characteristics and motion prediction of the spinning target are analyzed. Then, the Unscented Kalman Filter (UKF) is used to predict the motion state of the target. On this basis, a method of autonomous path planning of a free-floating space robot for target capturing is proposed, which is based on motion prediction and speed compensation. Simulations are carried out to verify the feasibility and validity of the proposed method.

In order to optimize the speed control performance of two-phase hybrid stepping motor, the impacts of the strong-coupled magnetic field and the time-varying parameters on the closed-loop control system are explored. According to the operating principle of stepping motor and relationship between winding back electromotive force and rotor position, an intelligent control method is proposed based on brain emotional learning model. This method is independent to the dynamic mathematical model of the motor, thus eliminating the effects of the time-varying parameters. Compared with Proportional Integral Derivative (PID) control, the proposed method can more effectively inhibit the vibration, increase the speed of response and improve the speed tracking precision. This control method is suitable for the applications with high requirements on response speed, precision and stability.

An intersection model between a simple broad boundary region and a simple region is proposed on the basis of RCC5. Based on the constraints of the simple broad boundary model an algorithm is developed, by which 11 achievable and complete topological relations are obtained. This paper establishes a model for representation and reasoning of the topological relations between a simple broad boundary region and a simple region. This model can be used to represent and predict the topological relations between typhoon wind circle area and specified island region. This method may provide guidance for anti-typhoon warning mechanism in island region.

A dynamic power management stochastic policy for non-stationary multi-task is proposed. First, device-requester utilization lookup table was constructed based on system message, and distribution was updated according to the actual time interval. Then, a Semi-Markov stochastic model was built, and the cost function and objective function were defined. The discount criteria optimization method based on linear programming strategy was given. The moment of decision and conversion state was pointed out. Experimental results show that, while considering the conditions of the performance constraints, the algorithm has good stability; delay rate is less than 0.10; competitive rate can reach 0.57. The algorithm reduces power consumption more efficiently than other policies, and is beneficial to the application in embedded systems.

Based on network calculus, a technique was proposed for analyzing communication delay bounds for individual flows in Networks on Chip (NoC) using Improved Asymmetric Multi-channel Structure (IAMCS) of router. The flow control blocking, switch blocking and channel blocking of IAMCS router were analyzed. Then, corresponding equivalent service models of them were constructed. By extending the router service model to the analysis of the entire network, the forward equivalent service analysis network was established. Furthermore, using the contention tree model, the equivalent service curves were computed for individual flows in the equivalent service analysis network, and then their delay bounds were derived. Experimental results show that the delay bound model can restrict the maximum delay of simulation, and the bounds is compact.

Based on Attribute-Based Encryption (ABE), a variety of access control schemes have been constructed in cloud computing. However, in these schemes, the ciphertext overhead goes linearly with the number of attributes used in encryption. To address this concern, a CCP-ABE (Constant-size Ciphertext Policy ABE) based access control scheme is proposed. The original data is encrypted by a symmetric key; then symmetric key is encrypted under an AND-gate access policy. Only the user who possesses a set of attributes that satisfy the policy can recover the symmetric key. The security of the proposed scheme is proved based on security of the CPA (Chosen Plaintext Attack) secure CCP-ABE scheme. Moreover, a method of constructing CCA (Chosen Ciphertext attack) secure CCP-ABE schemes is introduced. Performance analysis indicates that the ciphertext overhead over the number of attributes included in ciphertext is constant-size rather than linearity.

A new method for long-term Intuitionistic Fuzzy Time Series (IFTS) forecasting is proposed. By employing the sliding window scheme and vector quantization technique, the non-matching problem of intuitionistic fuzzy rules is solved efficiently. Meanwhile, the distribution characters of the uncertain time series data system are reflected accurately. The long-term forecasting accuracy of time series in the complex environment is improved, thus greatly extending the IFTS forecasting application. Finally, the experimental results validate the efficiency and advantage of the proposed algorithm.

An image encryption algorithm based on dynamic DNA coding is proposed, which uses the spatiotemporal chaotic model as the core control function. In this algorithm, the indexes are created according to the status values of the coupled map lattices. Then, the DNA coding rules are determined by the indexes. Since the pixels are coded as different DNA bases with variable rules, the security of the encryption algorithm is improved. Moreover, the Cipher-block chaining mode and chaos iteration are employed in the encryption process to enhance the confusion and diffusion of the algorithm. Simulation experiments show that the proposed algorithm has good security and high potential to be applied in image encryption.

A model of Auto Regressive (AR) algorithm is established to predict clock error. The model takes the advantage of strong abilities of non-linear operation and fault toleration of Least Square-Support Vector Machine (LS-SVM) to determine the parameters of AR. It also optimizes the LS-SVM parameters by Particle Swarm Optimization (PSO), which could search the best target fast. In order to overcome the shortcoming that PSO always plunges into local extremum and becomes premature, Chaos theory is introduced into positional initialization and local extremum condition, which improves particles' ergodicity and the ability of optimization, accordingly the algorithm as a whole is optimized. The algorithm is tested by satellite clock error data. The results show that the algorithm can achieve sub-nanosecond prediction precision, thus improving the satellites' time service and navigation.

In this paper, the cross power spectrum estimation theory and method were studied in detail. The Levinson algorithm based on cross-spectrum of the Autoregressive (AR) model parameter estimation was proposed. The good spectral estimation performance of the proposed Levinson algorithm was verified by constructed digital simulation models. Then, the simulation platform was constructed in the measurement of noise background, and the anti-jamming performance of the Transform Domain Communication System (TDCS) based on the proposed Levinson algorithm was investigated. Simulation results show that the proposed method can effectively suppress the measurement noise and the TDCS maintains a strong anti-jamming capability. Thus, the proposed method can improve the communication quality and utilization of the spectrum resources.

We consider the problem of estimating the Directions of Arrival (DOA) of broadband Chirp signal sources using a sensor array. Since the Fractional Fourier Transform (FRFT) can rotate the time-frequency plane, the frequencies of Chirp signals are concentrated by a properly chosen rotational angle, and the direction array is also obtained in FRFT domain. By this way, the broadband DOAs estimation is then successfully processed using the well existing narrowband DOA estimation algorithms. Simulation results demonstrate that the proposed method is quite simple and has much better performance compared to the methods such as the Coherent Signal Subspace method.

According to the characteristics of Wireless Sensor Network (WSN) and the profile detecting system, a data processing method based on WSN is proposed. In this method, first, the sample features are extracted by principal component analysis; then, the features of different samples were fused using accumulate mode. A mathematical model was given and on the basis of this model, a novel algorithm of special object recognition based on sparse representation in multiclass fusion sample was proposed. This algorithm recognizes the special target according to distribution of the main non-zero coefficients under an over-complete dictionary. Numerical simulation and experimental results demonstrate the effectiveness of the proposed algorithm, the comprehensive performance is better than the traditional methods.

An improved modular Two-directional Two-dimensional Principle Component Analysis (2D(PCA)) with eigen weight for face recognition is proposed. First, the image is divided into sub-blocks and the features are extracted by modular 2D(PCA). Then, the feature weight is assigned to each sub-block of every image according to the contribution for recognition of the sub-block. Finally, the testing samples are classified by nearest neighborhood classification of weighted distance. The contribution of each sub-block is determined self-adaptively according to the proportion of local feature information in eigen space. This algorithm does not need any prior knowledge. Experimental results show that the recognition rate of the proposed algorithm is effectively improved.

A segmentation method on the sonar image of a small underwater target is proposed. In this method, the gray-level threshold for segmentation is acquired via the minimum symmetric Tsallis cross entropy that is based on one-dimensional bound histogram. In this method, first, the speckle noise of the sonar image is suppressed. Second, the bound set is constructed according to the restriction in the gray-level values of both pixels and their neighborhood averages, and the one-dimensional bound histogram corresponding to that bound set is established. Third, the gray-level threshold for segmentation is determined according to the minimum symmetric Tsallis cross entropy based on the one-dimensional bound histogram. Finally, the isolated areas in the threshold image are removed. Experimental results show that the proposed method is well adequate for the images with a nonideal bimodal histogram; it has better antinoise performance than the existing methods based on the entropy of the one-dimensional bound histogram.

Based on the mechanism of human visual attention, five features are chosen to simulate the process of subjective quality assessment of fingerprint images. Among these features, two of them are extracted by two proposed methods, a minutiae reliability assessment based on Polar Coordinates Centrum Sensitivity (PCCS) and a gray-scale image contrast based on Otsu algorithm. Experimental results show that this feature set on both Error Back Propagation (BP) Neural Network and Support Vector Machine (SVM) gives high classification accuracy.

Using traditional pulse analysis method could bring serious influence on the accuracy and reliability of pulse signal feature detection. In order to overcome the shortcoming of the traditional threshold algorithm in peak detection of pulse signal, also to avoid the risk caused by the interference segment of pulse signal on signal analysis, a dynamic threshold method was presented to extract the peak of pulse wave. The symbolic aggregate approximation algorithm was timely used according to the difference and amplitude threshold to detect interference segment in the process. The pulse signals collected in the experiment of video display terminal fatigue were analyzed by this method. The results show that the proposed method can accurately extract the pulse peak and the position. It is obviously superior to the traditional method.

A fast blind spectrum sensing method using Sevcik fractal dimension in frequency domain is proposed. First, the Sevcik fractal dimension in frequency domain of the received signal is calculated. Then according to the difference of Sevcik fractal dimension characters between signal and noise, the calculation result is compared with the predefined threshold to determine whether the primary user exists. Compared with existing spectrum sensing methods, the proposed method has some advantages, such as insensitive to noise uncertainty, not requiring priori knowledge, and high detection probability in low SNR situation. Furthermore, it consumes less calculation time. This method can be applied to fast blind spectrum sensing in the situation of low SNR and noise uncertainty. Monte Carlo simulation results show that its average detection probability of signals with 7 modulation types can reach 100% when SNR is larger than -12 dB with ±5 dB noise uncertainty.

To overcome the disadvantages of high computational complexity of maximum likelihood detection algorithm and the poor performance of the Least Square (LS) channel estimation, a new joint estimation and detection algorithm is proposed. In order to improve the system effectiveness, LS algorithm is applied to initialize channel and Space-alternating Generalized Expectation-maximization (SAGE) algorithm is employed to process channel iterative estimation. The proposed algorithm combines the improved Grover quantum search algorithm in signal detection. Theoretical study and simulation results show that bit error rate performance of proposed algorithm is better than that of traditional joint detection algorithm. Ideal channel estimation under the maximum likelihood algorithm can be approached by the proposed algorithm with low complexity.

To improve the orthogonal performance of polyphase sequences of transmitting signals for Multiple-Input Multiple-Output (MIMO) radar, a modified biogeography-based optimization algorithm, POBBO, is proposed for designing orthogonal waveform of polyphase sequences for radar. In this proposed algorithm, the Biogeography-based Optimization algorithm (BBO) is improved. The Habitat Suitability Index (HSI) for individuals is directly adopted to determine the immigration rate and the emigration rate, which significantly simplifies the original method. This reflects the real-time quality for individuals meanwhile shortens the time loss by sorting. Simultaneously, the piecewise logistic chaotic map is introduced to improve the variation mechanism and achieve the effective exploitation for new individuals. In order to obtain the waveform of polyphase sequences with better orthogonal performance, POBBO utilizes the migration and the mutation among the habitats of BBO to interact and improve the HSI. Numerical experiments show that POBBO is competitive with other waveform design algorithms in terms of search accuracy and speed.

Defines and extracts minutiae ratio, tight pair-wise prototype distance, grid set distance, and Housdorff distance from minutiae as four auxiliary features. Fingerprint recognition is realized by fusing with an existed minutiae based matching method at the score level. Experiment results on databases of FVC2000, FVC2002 and FVC2004 for international fingerprint verification competition indicate that fused with the discriminating information of the unmatched minutiae, the performance of the fingerprint system is noticeably promoted. The results also verify that unmatched minutiae truly contain discriminating information.

Traditional Time-frequency Peak Filtering (TFPF) usually causes errors at peaks and valleys of valid signal. This study proposed a parallel Radial Trace Transform (RTT)-TFPF with x-interpolation method to reduce these errors. The proposed method uses TFPF to eliminate noise after mapping seismic signals from coordinates of offset and traveltime to those of apparent velocity and traveltime, namely filtering the signals along the direction of the radial trace in the time-space domain. The effect of the different slope of radial trace on the unbiased estimation of TFPF was discussed. Simulation experiments of synthetic seismogram were carried out to compare the traditional TFPF and the RTT-TFPF with different slopes. The results show that when the selected radial traces and events are parallel or the angles between them are small, the proposed method can make the signals better meet the condition of unbiased estimation in one window length, reduce the errors of the peaks and valleys of filtered signal, and improve the property of amplitude-preservation, the SNR of the proposed method can increase about 5 dB.

Based on one-dimensional layer model, the signal characteristics of the detection with probing depth of 1000 m were analyzed using the forward modeling. Furthermore, the basic performance parameters of the receiver sensor were determined. The physical model of the sensor was built, the sensor frequency characteristics under different matching conditions and their impacts on sensitivity were analyzed. On the basis of constructing the equivalent model of noise sources, the variations of noise sources with frequency characteristics were given. At the same time, the solution to inhibit high source impedance was given. An anomaly coil was used in field experiment in order to test the output characteristic of the sensor. Experiment results agree with theoretical calculation, and noise characteristic of the sensor can effectively meet the detection need.

Debris flow is one of the main reasons to destroy highway, so debris flow danger ec=valuation is an important issue in reducing the harm of debris flow to highway. Evaluation factors of debris flow danger were retrenched based on path analysis method, and the factors which greatly influence the debris flow danger evaluation were selected, including the main channel length, the largest volume of once flow, the drainage area, the length ratio of sediment supplement, valley relative height, bending coefficient of major ditch bed and maximum rainfall in 24 h. Then extension method was applied in debris flow danger evaluation. The site of Da-Xi-Gou regional debris fully was selected for this study. Calculation were done according to the correlation functions of extension set about the four types of risk levels of the correlation, which are K₁(p) = -0.288 9, K₂(p) = 0.034 4, K₃(p) = -0.626 5, K₄(p) = -0.750 4 respectively. So the debris flow risk level of the gully is evaluated as moderate risk. The evaluation results are consistent with that of the actual survey Liu Xilin model, and the correlation method. The selection of evaluation factors is reasonable and the proposed evaluation method is feasible, which could provide a basis for mitigating debris flow disasters along highway.