Patch-based vehicle logo detection with patch intensity and weight matrix

A patch-based method for detecting vehicle logos using prior knowledge is proposed.By representing the coarse region of the logo with the weight matrix of patch intensity and position,the proposed method is robust to bad and complex environmental conditions.The bounding-box of the logo is extracted by a thershloding approach.Experimental results show that 93.58% location accuracy is achieved with 1100 images under various environmental conditions,indicating that the proposed method is effective and suitable for the location of vehicle logo in practical applications.

Searching high gray scale FPD scanning matrix based on PSO

With the increase of gray scale and flat panel display （FPD） size, subspace bitwise scanning strategy can be replaced traditional scanning method to cut down frame frequency. However, the direct searching strategy （DSS） becomes unfeasible to obtain corresponding high gray scale scanning matrix. Thus, particle swarm optimization （PSO） is introduced to accelerate searching for high gray scale weights scanning matrix （WSM） with its parallelism and global optimization feature. Finally a WSM of 256 gray scales is found out successfully with Matlab, which both gray linearity and scanning efficiency are satisfied.

Spatial weight matrix in dimensionality reduction reconstruction for microelectromechanical system-based photoacoustic microscopy

A micro-electromechanical system(MEMS)scanning mirror accelerates the raster scanning of optical-resolution photoacoustic microscopy(OR-PAM).However,the nonlinear tilt angular-voltage characteristic of a MEMS mirror introduces distortion into the maximum back-projection image.Moreover,the size of the airy disk,ultrasonic sensor properties,and thermal effects decrease the resolution.Thus,in this study,we proposed a spatial weight matrix(SWM)with a dimensionality reduction for image reconstruction.The three-layer SWM contains the invariable information of the system,which includes a spatial dependent distortion correction and 3D deconvolution.We employed an ordinal-valued Markov random field and the Harris Stephen algorithm,as well as a modified delay-and-sum method during a time reversal.The results from the experiments and a quantitative analysis demonstrate that images can be effectively reconstructed using an SWM;this is also true for severely distorted images.The index of the mutual information between the reference images and registered images was 70.33 times higher than the initial index,on average.Moreover,the peak signal-to-noise ratio was increased by 17.08%after 3D deconvolution.This accomplishment offers a practical approach to image reconstruction and a promising method to achieve a real-time distortion correction for MEMS-based OR-PAM.

Optimal strategy of searching FPD weights scanning matrix using GA-PSO

This paper discusses a kind of optimal method used for searching flat panel display （FPD） scanning matrix. The method adopts bionic algorithm： genetic algorithm （GA） and particle swarm optimization （PSO） algorithm. The method using single GA is more time-consuming, and the search efficiency is low in later evolution; the PSO algorithm is easily falling into the local optimal solution and appears the premature convergent phenomenon. Hence, a hybrid approach of GAPSO is found to optimize the search for high grayscale weights scanning matrix. Finally in the acceptable time, it finds a weight scanning matrix （WSM） of 256 gray scales with Matlab, whose scanning efficiency reaches 94.73% and the linearity is very good.

Research on consistency measurement and weight estimation approach of hybrid uncertain comparison matrix

The consistency measurement and weight estimation approach of the hybrid uncertain comparison matrix in the analytic hierarchy process （AHP） are studied. First, the decision-making satisfaction membership function is defined based on the decision making＇s allowable error. Then, the weight model based on the maximal satisfactory consistency idea is suggested, and the consistency index is put forward. Moreover, the weight distributing value model is developed to solve the decision making misleading problem since the multioptimization solutions in the former model. Finally, the weights are ranked based on the possibility degree approach to obtain the ultimate order.

A Note on the Spectral Radius of Weighted Signless Laplacian Matrix

A weighted graph is a graph that has a numeric label associated with each edge, called the weight of edge. In many applications, the edge weights are usually represented by nonnegative integers or square matrices. The weighted signless Laplacian matrix of a weighted graph is defined as the sum of adjacency matrix and degree matrix of same weighted graph. In this paper, a brief overview of the notation and concepts of weighted graphs that will be used throughout this study is given. In Section 2, the weighted signless Laplacian matrix of simple connected weighted graphs is considered, some upper bounds for the spectral radius of the weighted signless Laplacian matrix are obtained and some results on weighted and unweighted graphs are found.

Receding horizon H_∞ control for discrete-time Markovian jump linear systems

Receding horizon H∞ control scheme which can deal with both the H∞ disturbance attenuation and mean square stability is proposed for a class of discrete-time Markovian jump linear systems when minimizing a given quadratic performance criteria. First, a control law is established for jump systems based on pontryagin’s minimum principle and it can be constructed through numerical solution of iterative equations. The aim of this control strategy is to obtain an optimal control which can minimize the cost function under the worst disturbance at every sampling time. Due to the difficulty of the assurance of stability, then the above mentioned approach is improved by determining terminal weighting matrix which satisfies cost monotonicity condition. The control move which is calculated by using this type of terminal weighting matrix as boundary condition naturally guarantees the mean square stability of the closed-loop system. A sufficient condition for the existence of the terminal weighting matrix is presented in linear matrix inequality （LMI） form which can be solved efficiently by available software toolbox. Finally, a numerical example is given to illustrate the feasibility and effectiveness of the proposed method.

Control of static unstable airframes

The challenge and control problems of static unstable missiles are presented. The steady-state benefits of static instability are illustrated, while the corresponding control challenge is described both by the characteristic lag of airframe and the increment of necessary control usage. Control limitation led by unstable zero-pole pair is analyzed for preliminary design and evaluation. Linear control strategy is examined wherein two and three loop acceleration autopilots with different control usages are developed using an optimal control approach combined with frequency domain constraint. The weights selection and relation with system performance are detailed. Then the nonlinear backstepping recursive method is detailed to determine how well it is able to follow command and its engineering feasibility. The results show that a static unstable missile is controllable, while the actuator bandwidth is the crucial limited factor. There should be a compromise between overall performance and actuator payment.

PEMFC Fractional-order Subspace Identification Model

A proton exchange membrane fuel cell(PEMFC)is a new type of hydrogen fuel cell that plays an indispensable role in an energy network.However,the multivariable and fractional-order characteristics of PEMFC make it difficult to establish a practical model.Herein,a fractional-order subspace identification model based on the adaptive monarch butterfly optimization algorithm with opposition-based learning(ALMBO)algorithm is proposed for PEMFC.Introducing the fractional-order theory into the subspace identification method by adopting a Poisson filter for with input and output data,a weight matrix is proposed to improve the identification accuracy.Additionally,the ALMBO algorithm is employed to optimize the parameters of the Poisson filter and fractional order,which introduces an opposition-based learning strategy into the migration operator and incorporates adaptive weights to improve the optimization accuracy and prevent falling into a locally optimal solution.Finally,the PEMFC fractional-order subspace identification model is established,which can accurately describe the dynamic process of PEMFC.

Multi-channel signal parameters joint optimization for GNSS terminals

Traditional global navigation satellite system(GNSS)terminals for satellite navigation adopt independent channels to track the signals from different satellites, which results in a lack of information interaction between the channels. Inspired by the vector tracking idea, and drawing lessons from the principle that in the position domain the Taylor expanded pseudorange observations can be used for positioning via the least squares method, this paper proposes a novel least squares-based multi-channel parameter joint estimation(MPJE) method in the signal domain, which not only retains the advantages of channel fusion, but also maintains the flexibility and diversity of the localization algorithm. With achieving optimal carrier to noise ratio as the goal, the proposed method obtains the required code loop and carrier loop parameters for signal tracking in the domain of whole channels. Experimental results indicate that this method fully achieves the assistant fusion advantages of frequency lock loop(FLL), phase lock loop(PLL)and delay lock loop(DLL), making good use of the robustness and dynamic properties of the FLL and the measurement accuracy of the DLL, and is helpful for achieving stable and accurate signal tracking under weak signals and high dynamic stress environments.

A combined statistical model for multiple motifs search

Transcription factor binding sites （TFBS） play key roles in genebior 6.8 wavelet expression and regulation. They are short sequence segments with definite structure and can be recognized by the corresponding transcription factors correctly. From the viewpoint of statistics, the candidates of TFBS should be quite different from the segments that are randomly combined together by nucleotide. This paper proposes a combined statistical model for finding over- represented short sequence segments in different kinds of data set. While the over-represented short sequence segment is described by position weight matrix, the nucleotide distribution at most sites of the segment should be far from the background nucleotide distribution. The central idea of this approach is to search for such kind of signals. This algorithm is tested on 3 data sets, including binding sites data set of cyclic AMP receptor protein in E.coli, PlantProm DB which is a non-redundant collection of proximal promoter sequences from different species, collection of the intergenic sequences of the whole genome of E.Coli. Even though the complexity of these three data sets is quite different, the results show that this model is rather general and sensible.

Spectral clustering based on matrix perturbation theory

This paper exposes some intrlnsic chsracterlstlca of the spectral clustering method by using the tools from the mstrlx perturbation theory. We construct s welght mstrix of s graph and study Its elgenvalues and elgenvectors. It shows that the number of clusters Is equal to the number of elgenvslues that are larger than 1, and the number of polnts In each of the clusters can be spproxlmsted by the associated elgenvslue. It also shows that the elgenvector of the weight rnatrlx can be used dlrectly to perform clusterlng; that Is, the dlrectlonsl angle between the two-row vectors of the mstrlx derlved from the elgenvectors Is s sultable distance measure for clustsrlng. As s result, an unsupervised spectral clusterlng slgorlthm based on welght mstrlx （USCAWM） Is developed. The experlmental results on s number of srtlficisl and real-world data sets show the correctness of the theoretical analysis.

Inverse Problems for the Dirac Operator on a Star Graph

Following the previous work,we shall study some inverse problems for the Dirac operator on an equilateral star graph.It is proven that the so-called Weyl function uniquely determines the potentials.Furthermore,we pay attention to the inverse problem of recovering the potentials from the spectral data,which consists of the eigenvalues and weight matrices,and present a constructive algorithm.The basic tool in this paper is the method of spectral mappings developed by Yurko.

Parameter Optimization of Linear Quadratic Controller Based on Genetic Algorithm

The selection of weighting matrix in design of the linear quadratic optimal controller is an important topic in the control theory. In this paper, an approach based on genetic algorithm is presented for selecting the weighting matrix for the optimal controller. Genetic algorithm is adaptive heuristic search algorithm premised on the evolutionary ideas of natural selection and genetic. In this algorithm, the fitness function is used to evaluate individuals and reproductive success varies with fitness. In the design of the linear quadratic optimal controller, the fitness function has relation to the anticipated step response of the system. Not only can the controller designed by this approach meet the demand of the performance indexes of linear quadratic controller, but also satisfy the anticipated step response of close-loop system. The method possesses a higher calculating efficiency and provides technical support for the optimal controller in engineering application. The simulation of a three-order single-input single-output (SISO) system has demonstrated the feasibility and validity of the approach.

Application of the hybrid genetic particle swarm algorithm to design the linear quadratic regulator controller for the accelerator power supply

Purpose The purpose of this paper is to study a new method to improve the performance of the magnet power supply in the experimental ring of HIRFL-CSR.Methods A hybrid genetic particle swarm optimization algorithm is introduced,and the algorithm is applied to the optimal design of the LQR controller of pulse width modulated power supply.The fitness function of hybrid genetic particle swarm optimization is a multi-objective function,which combined the current and voltage,so that the dynamic performance of the closed-loop system can be better.The hybrid genetic particle swarm algorithm is applied to determine LQR controlling matrices Q and R.Results The simulation results show that adoption of this method leads to good transient responses,and the computational time is shorter than in the traditional trial and error methods.Conclusions The results presented in this paper show that the proposed method is robust,efficient and feasible,and the dynamic and static performance of the accelerator PWM power supply has been considerably improved.

A New Method for Calculating Priorities in AHP

On the basis of weight matrix, this paper presents a new optimizing approach to calculate priorities in the analytic hierarchy process(AHP), this method is a development of the synthetichierarchy method, which was proposed by Lipovetsky in [2], it enables the united consideration of allhorizontal and vertical connections of a hierarchical system in a single optimizing objective functionbased on statistical models of the synthesis process. The ultimate priority vector is proportional tothe solution of a linear system or an eigenproblem of a matrix. A numerical example is also given.Theoretical analyses and the numerical example all show that the method is more practical and needsless time for obtaining priorities than that of IZ].

Insights on the solubilization products after combined alkaline and ultrasonic pre-treatment of sewage sludge

This work provides insights on the solubilization products after a simultaneous combination of alkaline and ultrasonic （ALK ＋ ULS） pre-treatment of sewage sludge. Soluble chemical oxygen demand （SCOD） increased from 1200 to 11,000 mg/L after such treatment. Organics with molecular weight around 5.6 kDa were solubilized because of the synergistic effect of ultrasound and alkali. Organics with molecular weight larger than 300 kDa increased from 7.8% to 60%, 16% and 42.3% after ULS, ALK and ALK ＋ ULS treatment, respectively. Excitation emission matrix fluorescence spectroscopy analysis identified soluble microbial product-like and humic acid-like matters as the main solubilization products. Sludge anaerobic biodegradability was significantly enhanced with the simultaneous application of ALK ＋ ULS pre-treatment. ALK ＋ ULS pre-treatment resulted in 37.8% biodegradability increase compared to the untreated sludge. This value was higher compared to the biodegradability increase induced by individual ALK pre-treatment （5.7%） or individual ULS pre-treatment （20.7%） under the same conditions applied.

Splicing Signals in the Human Hemoglobin Genes at the Sequence and Folding Levels

Identification of the splice sites is a critical and tough issue in eukaryotic genome annotation. Here, a statistical study is introduced for detecting the splicing signals in the human hemoglobin （Hb） pre-mRNAs by using the approaches of regional pairwise alignment, splicing weight matrix scoring, and dynamic extended folding. First, the regional pairwise alignment results show that the coding regions of the human Hb genes are at a high level for both conservation and fluctuation. Second, the weighted matrix scoring results indicate that, although the authentic splicing motifs are always scored the highest in a sequence, the sequence motif alone is inadequate to precisely define the splice sites. Finally, we deduce the RNA frame structures by applying an extended folding approach to analyze the stable folding elements. We find out that the splice sequences tend to take stretching and partially paired conformations, which benefit recognition and competitive binding of the splicing factors. These results indicate that precise splicing is an integrated effect of multiple mechanisms of signal recognition at the level of sequence and structure.

The Linear Unicyclic Hypergraph with the Second or Third Largest Spectral Radius

The spectral radius of a uniform hypergraph is defined to be that of the adjacency tensor of the hypergraph.It is known that the unique unicyclic hypergraph with the largest spectral radius is a nonlinear hypergraph,and the unique linear unicyclic hypergraph with the largest spectral radius is a power hypergraph.In this paper we determine the unique linear unicyclic hypergraph with the second or third largest spectral radius,where the former hypergraph is a power hypergraph and the latter hypergraph is a non-power hypergraph.

THE STABILITY OF A KIND OF DISCRETE-TIME HOPFIELD NEURAL NETWORKS WITH ASYMPTOTICAL WEIGHTED MATRICES

In this paper, the authors analyze the stability of a kind of discrete-time Hopfield neural network with asymptotical weighted matrix, which can be expressed as the product of a positive definite diagonal matrix and a symmetric matrix. We obtain that it has asymptotically stable equilibriums if the network is updated asynchronously, and asymptotically stable equilibriums or vibrating final stage with 2 period if updated synchronously. To prove these, Lassale＇s invariance principle in difference equation is applied.