WSN localization algorithm based on RSSI correction

In order to solve the problem that there is large errors in DV-Hop algorithm in network topology environments, a modified RSSI-based WSN localization algorithm RMDV-Hop (RSSI Modify DV-Hop)is presented in this paper. The algorithm limits the maximum number of hops and uses RSSI value to modify its hop value when hop of an anchor node is 1. The first N anchor nodes with greater RSSI value is chosen as reference anchor nodes and per hop distance error of the reference anchor nodes are used to weight average hop distance of the unknown node. Finally,a total least squares method is used to calculate the coordinates of the position of the unknown node to achieve overall improvement of RMDV-Hop localization algorithm and improve the positioning accuracy. The simulation results show that the positioning accuracy and stability of the improved algorithm has been significantly improved than those of the original algorithm.     

Optimal sensor deployment scheme for heterogeneous wireless sensor networks

For the high density of distributed heterogeneity nodes in wireless sensor networks (WSNs), the optimal sensor deployment is studied. A cost optimal heterogeneous sensor deployment scheme based on genetic algorithm is proposed. The cost of sensor node deployment is used as objective function for optimization computation subjected to network coverage and fault tolerance to obtain the suitable types and positions of the sensors. The algorithm can be used for boolean sensing model as well as probabilistic sensing model. The simulation results demonstrate that the proposed algorithm converges fast toward the optimal solutions and reduces the cost of sensor deployment, which is feasible for heterogenous nodes deployment in WSNs.     

A clustering algorithm based on link availability for MANET

The cluster topology management in the MANET network is studied in. The classic Lin-Gerla clustering algorithm is improved to increase the logical topological stability. By considering the node mobility in the communication systems, the notion of relative motion is introduced, and the nodes more stable are chosen as the cluster-heads, which effectively increases the stability of mobile network with Random Direction Model. Regarding the possible high concentration, a fast cluster splitting method is proposed for cluster maintenance. The simulation and performance analysis for the improved algorithm are given.     

A cooperative localization algorithm for wireless sensor networks

Aiming at the shortcomings of the existing RSS(received signal strength) based localization algorithm for wireless sensor networks (WSN), a cooperative localization algorithm (CLA) is proposed. A reference anchor node is introduced to tolerant some minor error including the node position error. Dixon detection method is applied to remove abnormal RSS values, while the standard deviation threshold of RSS and learning model are introduced to reduce the RSS ranging error and effectively improve the precision. Simulation experiments are performed to evaluate the performance of the proposed algorithm. The results demonstrate that the localization accuracy is improved effectively, while the stability and robustness are better.     

An improved HEED clustering algorithm for Wireless Sensor Network

In wireless sensor network, routing protocols which based on clustering have the advantages of energy consumption, topology management and data fusion. The HEED protocol, which generates cluster heads based on distributed algorithm, drives up the rate of clustering and creates well distributed cluster heads. However, it does not consider the mobility of nodes in the network. When the distance between neighbor nodes has changed, the AMRP method which decides the node belongs to different cluster heads would cause problems such as high energy consumption, short lifetime of network and so on. Responding to these problems, the paper proposes the S HEED, a clustering algorithm based on stability, which chooses the stability as a parameter of nodes when choosing a cluster head. With S HEED algorithm, the high energy consumption problem among cluster nodes and cluster heads caused by the mobility is tackled. The simulation experiment demonstrates that the S HEED algorithm lower the energy consumption of cluster heads and prolongs the network lifetime.     

Algorithm of removing outliers in SVR

The outlier and the measurement that an outlier does not fit the theoretical model in the regression problems are defined. The relationship between the theoretical model and the regression model in the regression problem is analyzed. An approximate theorem is proposed and verified by deleting outlier one by one to construct SVR to approximate the theoretical model. An algorithm of detecting outliers in the SVR problems is constructed based on the approximate theorem. The theoretical analysis of the convergence and effectiveness of the proposed algorithm is given. Then, the step-by-step search algorithm is introduced to improve the outlier removing algorithm to remove outliers in SVR with large-scale samples. The theoretical analysis shows that the improved algorithm is convergent and effective. Finally, the samples produced by two test functions and the samples in UCI data set are used for simulation, and the results show that the proposed algorithm is effective and robust.     

On-demand routing algorithm based on load balancing and mobility prediction in wireless mobile Ad hoc network

The traditional routing protocol for wireless mobile ad hoc networks is unable to achieve balanced energy consumption and could not adapt to the dynamic topology changes well.A novel on-demand rooting algorithm is proposed based on load balancing and mobility prediction.The proposed rooting algorithm excludes the unstable links in routing discovery,and allows the node with more energy forward the routing request packet preferentially.In addition,it adopts the active local routing recovery strategy by predicting the link connection time,and finishes the repair work before the link being actually failure.The simulation experiments demonstrate that,comparing with the traditional AODV protocol,with slight increase of the rooting control overhead,the proposed algorithm increases the average packet delivery ratio,decreases the average end-to-end delay of the data packets,and achieves load balancing in the network and prolong the life-span of the network,which shows the proposed algorithm is highly practical.     

Computation of the Wavelet and Scaling Functions Using Coefficients of Wavelet Filter

To associate the discrete wavelet transform with the continuous wavelet transform, an iterative convolution algorithm is given by analyzing the and scaling function using coefficients of wavelet filter. usually used methods of the computation The way of judging the convergence of improved algorithm on of the wavelet function iterative convolution is given. The advantages of improved algorithm is analyzed. The experimental result shows that the modified algorithm is effective.     

A borrowed address based on efficient distributed address assignment algorithm in ZigBee networks

The borrowed address algorithm can solve the orphan problem made by the restriction of threshold of children when DAAM(distributed address assignment mechanism) assigns the addresses for the nodes in ZigBee networks. The exited borrowed algorithms only can increase the success ratio of address assignment, but their overhead and times spend on founding net cost much. To address the problem, we propose an efficient borrowed address assignment algorithm EDAA BA (efficient distributed address assignment algorithm based on borrowed address). To control the overhead and time spend on founding net, it borrows addresses firstly from the descent nodes in same branch for the orphan router nodes, adds the mechanism of immediate reply of borrowed message, and assigns the remainder addresses unused by DAAM in the 16 bits addresses for the orphan end devices. Theoretical and simulation analyses show that our algorithm outperforms DAAM and two of its present improvement algorithms in terms of the overhead and time spent on forming network, under the premise of better success rate of address assignment.     

Weighted fusion algorithm for frequency estimation of the short signal with the same frequency and length

For high precise frequency estimation of the short sinusoid signal at low signal-to-noise ratio (SNR), a weighted fusion algorithm for frequency estimation of the short signal with the same frequency and length (SFL-Signal) is proposed. The spectrum model of SFL-Signal and the phase compensation matrix with phase coherent and noise cancellation are constructed. Secondly, the SFL-signal spectrum is weight-fused with the phase compensation matrix to obtain the result almost the same as that of the spectrum of the phase-coherent sinusoid signal. Consequently, high frequency estimation precision is obtained with spectral peak searching of the weight-fusion spectrum. Algorithm analysis and simulation results show that, compared with the existing methods,the proposed algorithm works better in term of precision, calculation complexity, noise immunity, and fits for any type of SFL-Signal.     

Optimization algorithm for forward problem with electric fields of defective insulator

The defective insulator can be detected by measuring electric field, however, the electric field calculation accuracy of the insulator strings is low. Charge simulation method (CSM), which is optimized by genetic algorithm (GA), is adopted to calculate high voltage electrostatic field. The optimal method principle and feasibility analysis is given. The objective function and optimization model of electric field distribution around insulator strings are constructed and analyzed. The results of calculation and analysis demonstrate that adopting the potential of check points near insulator strings as objective function and using GA to optimize the charge of simulation charge, better performance can be achieved for improving ability of global optimization, calculating precision, searching speed, simulating precision of CSM and accuracy of diagnosing defective insulator in the insulator strings.     

Application of improved genetic algorithm to locating and sizing of distributed generation

A Prüfer-coded genetic algorithm based on the decimal number of nodes is proposed and it is used to solve collaborative optimization planning of access solution of distributed generation(DG)and structure of distribution network.Using graph theory to generate theoretically feasible topology structureand the access nodes and the installed capacity of distributed generation are coded by the Prüfer number.The coding method makes the distribution network operation structure and the access solution of DG combine into the evolution problem of the same chromosomal gene.The length of the chromosome coding of this method is shorter than binary encoding.This solution takes full advantage of the Prüfer-coded to improve computational efficiency and convergence rateand makes some restrictions and improvements in some key parts of the algorithm to solve the problem illegal solution.Finallyfeasibility and superiority of the algorithm is validated by a case study.     

A cooperative spectrum sensing algorithm with double-threshold relative distance weighting

Abstract：The single-node energy detection has the drawbacks of low accuracy and “Hidden terminal”, while the cooperative spectrum sensing algorithms usually use equivalent weights for data fusion instead of considering the influences to the detection performance resulting from the communication environment of different nodes. In order to solve these problems, a novel weighted cooperative spectrum sensing algorithm is proposed. The proposed algorithm is based on the double-threshold energy detection. According to the relation between the single-node dual-threshold setting and the node perceiving performance, the single-node dual-threshold relative distance is used as a credit for weighted cooperative data fusion. The simulation result proves that, compared with the single node double-threshold energy detection and the cooperative spectrum sensing algorithm based on OR-rule, the proposed algorithm can achieve reliable sensing performance with low SNR.     

A FAST ALGORITHM FOR DIGITAL SIMULATTON OF HVDC SYSTEMS

After considering the features of the differential equations which have described the dynamic behaviours of HVDC systems, a fast algori -thm is presented for these equations. Compared with the fourth Runge-Kutta Method,this method has less amount of calculation with the same precision, numerical stability and other properties. Therefore, the use of the method has greatly increased the speed of the digital simulation of HVDC systems.In this paper an example of calculation is given, and the results obtained hv using this example are compared with the results obtained by calculating with the fourth Runge-Kutta Method. The speed of simulation by using this method is about 1.8 timss as fast as that by using the fourth Runge-Kutta Method.     

An improved localization algorithm based on RSSI for landslide monitoring

In order to overcome the existing problems of low automation, high cost and difficult to implement in the area of landslide monitoring, this paper presents a new method of RSSI (Received Signal Strength Indicator)based positioning technology without any one-off instruments to monitor landslide surface displacement. By adding weighted factors, the improved positioning algorithm can estimate the parameters of the path loss model dynamically and calculates the communication distance of network nodes in real-time, which can improve positioning precision and reduce the impact of environmental changes on it. The MATLAB experiments show that, compared with the traditional RSSI based localization algorithm using fixed pass loss model, the improved algorithm could significantly reduce the average error.     

Simulation of the constant modulus blind equilibrium algorithm with variable step size based on the mean square error

The mathematic models and basic theory of constant modulus algorithm (CMA) for blind channel equalization are introduced. An improved algorithm with variable step size is proposed based on CMA. The improved algorithm uses the mean square error (MSE) to obtain the new variable step size to solve the contradiction between the convergence rate and accuracy in traditional CMA with fixed step. To smooth the MSE learning curve for easy comparison, an ensemble average technique is used to analyze the performance of convergence with different step sizes. The theoretical analysis and the simulation results show that the improved algorithm is superior to the traditional constant modulus(CM) in terms of convergence speed and residual error.     

Fast algorithm for apparent resistivity calculation based on back propagation neural networks

To avoid the complex numerical calculation for the electromagnetic field and determine underground abnormality, a neural network based method is proposed. In consideration of turn off transmitter current, the effect of a linear ramp turn off current on transmitter is corrected. The characteristics of transient expression and the traditional calculation algorithm for apparent resistivity are analyzed, and a predigest structure of network is obtained based on the kernel expression. The three layer back propagation(BP) neural network is trained by using sample data in homogeneous half space, and its number in hidden layer was determined. The method proposed is compared with two traditional calculation methods with simulation experiments. The result demonstrates that BP neural network has a high speed of processing data and is useful in explanation of the transient electromagnetic method.     

Feed-rate-controlled method of iterative algorithm for curve interpolation

In order to maintain a high machining accuracy and a constant speed feed-rate in CNC machining and improve the machining capability of CNC in handing complex part,the complicated interpolation algorithm needs to be used in CNC interpolation,which is time-consuming for large amount of computation,thus the machining speed is influenced. To solve this problem,based on the principle of parametric curve paths CNC interpolating,it is pointed out that Taylor series and iterative algorithm,given curve,using the chord length and the interpolation point,accurately calculate the next interpolation points. In the number of iterations and iterative error are less than the set value when the end of the iteration,next interpolation points can be calculated,and keep the current point and speed,otherwise continue iterative algorithm until they meet the requirements,feed-rate-controlled method based on iterative algorithm for curve real-time interpolation has also been given. The simulation results demonstrate that the proposed algorithm can satisfy the machining of a variety of different parametric curves. Compared with the conventional interpolation algorithm,it features are high university for machining,small computational a mount small feed-rate error and high computational accuracy,thereby greatly shorting the processing efficiency.     

QRS complexes detection using quadratic b-spline wavelet transform algorithm

Aiming at the low accuracy and low adaptability of wave detection, a QRS complexes detection algorithm is proposed based on quadratic b-spline wavelet, while combined with binary search algorithm and arc approximating curve algorithm. The signal is decomposed with quadratic b-spline wavelet through Mallat algorithm and the R wave is detected by adjusting the threshold with binary search and modulus maximumizing. The T wave and P wave are detected by using arc approximating curve algorithm based on the least square. This algorithm is certified with the ECG signals from MIT-BIH database and is demonstrated that the algorithm enhanced the adaptability of R wave detection and improved the accuracy of T wave and P wave detection. The simulation experiment shows that the improved algorithm can effectively improve the automatic detection capabilities of ECG signals.     

Modal Shape Analysis Methods of Machine Structure

The iterative Lanczos-reduce method for sensitivity analysis, the Guyan condensed method and the iterative synchronous vector methods in finite element modal are studied in order to solve the dynamic characteristic of complicated machine system. The primary reasons influenced on calculation precision are pointed out. The principia of master freedom for Guyan condensed method are put forward. The calculation precision of three methods is compared with the same standard finite element model. The iterative Lanczos-reduce method for sensitivity analysis is proved to be optimum analysis and the eigenvalue of arm in work device of hydraulic excavator in finite element model is solved with iterative Lanczos-reduce method for sensitivity analysis. The theory basis is provided for reasonable choose to solve the dynamic of complicated machine structure.