摘要:As an online learning algorithm,reinforcement learning,which obtains the optimal policy with the maximum expected cumulative reward by interacting with the environment,is mostly based on the stationary Markov Decision Process (MDP) but however is unable to deal with problems of the non-stationary case because traditional reinforcement learning algorithms cannot be used to learn an optimal policy directly due to the failure of MDP model after the agent once interacts with the environment.Hereby,a novel policy search algorithm based on a formula set (FSPS),which is generated by features extracted from the collected historical sample trajectories,was proposed.The algorithm adopted the formula with the best performance as the optimal policy.The algorithm also took advantage of concept of transfer learning by transferred the learned policy between two similar MDP distributions,where the performance of the transferred policy mainly depends on the distance between two MDP distributions as well as the performance of the learned policy in the original MDP distribution.Simulation results on the Markov Chain problem show that the algorithm can solve the problem of the non-stationary case quite well.
关键词:reinforcement learning;policy search;policy transfer;non-stationary environment;formula set
摘要:In order to rapidly construct software based on service-oriented architecture under dynamic running environments of Internet and to satisfy various requirements of users,an automatic service-composition evolution approach based on global dependence network (GDN) is proposed.It can automatically execute defined evolution operations on existed composited service according to evolution requirements.After that,it continues to execute reverse evolution reasoning and positive evolution reasoning based on the GDN from each evolution point.Then,it will automatically generate evolution results of composited service.An actual application is given to illustrate the entire evolution procedure.This application shows the correctness and effectiveness of the approach,which helps to reduce the cost and the cycle of software development.
摘要:As a parallel computation framework,Spark does not have a good strategy to select valuable RDD to cache in limited memory.When memory has been full load,Spark will discard the least recently used RDD while ignoring other factors such as the computation cost and so on.This paper proposed a self-adaptive cache management strategy (SACM),which comprised of automatic selection algorithm(Selection),parallel cache cleanup algorithm (PCC) and lowest weight replacement algorithm (LWR).Selection algorithm can seek valuable RDDs and cache their partitions to speed up data intensive computations.PCC clean-up the valueless RDD sasynchronously to improve memory utilization.LWR takes comprehensive consideration of the usage frequency of RDD,the RDD's computation cost,and the size of RDD.Experiment results show that Spark with our selection algorithm calculates faster than traditional Spark,parallel cleanup algorithm contributes to the improvement of memory utilization,and LWR shows better performance in limited memory.
关键词:parallel computing;cache management strategy;Spark;resilient distribution datasets
摘要:Signal sparsity is directly related to the determination of sampling rate and the construction of measurement matrix in compressive sensing.However,the sparsity order is often unknown or time-varying.In this context,investigating blind sparsity order estimation (SOE) techniques is an open research issue.To address this,asymptotic random matrix spectrum analysis theory was used to derive the asymptotic eigenvalue probability distribution function (AEPDF) of the measured signal's covariance matrix.Then,the paper used the relation between the measurement energy and AEPDF to further deduce the corresponding relation between the sparsity order,compressive rate,SNR and the measured signal energy.Subsequently,based on this relation,a technique to estimate the sparsity order using the measured signal energy was proposed.Simulation results show that the proposed algorithm can gain higher estimation performance with lower computational complexity compared with the existing algorithm.And the estimation accuracy can be enhanced by increasing the sampling overhead.
关键词:compressive sensing;sparsity order estimation;random matrix theory;stieltjes transform
摘要:In inverse synthetic aperture radar,the difficulty of motion compensation,the low imaging efficiency and resolution of sparse apertures for non-cooperate targets is a challenge problem.To solve the problem,a novel motion compensation and fast imaging method is proposed in this paper.First,the motion compensation is converted into a multi-parameters estimation problem.In order to accomplish the motion compensation,golden selection search (GSS) is adopted to estimate the multi-parameters.Second,the ISAR echoes' feature changes as range cell changing.To realize azimuth imaging efficiently,a matrix form of Nesterov linearized Bregman iteration (MNLBI) algorithm is proposed and the basic iteration scheme is presented as well.The method to speed up convergence of MNLBI is also given.Finally,the robustness to noise and computation is analyzed.The simulation and real data results show the effectiveness of the proposed method.
摘要:In order to solve the problem of sample particles impoverishment,an improved resampling particle filter is presented.It is based on the space distribution and time series analysis.The most important particle that has higher temporal correlation between the particle's path and observation path in particle propagating is chosen.It can avoid the problem in the traditional resampling algorithm that only the particle's weights are considered,and the low weighed particles have the risk to be thrown away.Thus the problem of particles impoverishment is weakened and the estimate accuracy is improved.By the two-sample Kolmogorov-Smirnov Test,a proof is given that the particles that are resampled by the improved algorithm and the original particles belong to the same distribution.The proposed approach,verified by simulations,indicates that its accuracy is better than traditional methods for the nonlinear system state estimation,especially when the number of initial sampling particles is small.
关键词:nonlinear estimation;residual resampling;Time series analysis;Kolmogorov-Smirnov test
摘要:Tag collision avoidance is a critical issue in RFID system.In order to further improve the performance of RFID system and reduce the computation complexity,an efficient idle slots elimination anti-collision algorithm based on binary splitting(ISE-BS) is proposed.In ISE-BS,one bit control flag signal is introduced to transmit before data exchange,where tag collision can be informed by control signal and the unnecessary data exchange between a reader and tags can be further avoided.Since the idle slots during BS algorithm are eliminated by ISE-BS,coordination transmission time of identification process is saved.Simulation results show that the proposed ISE-BS algorithm achieves throughput of 0.4065 and time efficiency of 0.3247,outperforms the existing anti-collision algorithms.To the view of implement,we compare the floating point operations(FLOP) cost of various algorithms.The results show that the proposed algorithm significantly reduces the system's complexity.
关键词:radio frequency identification;anti-collision;throughput;time efficiency
摘要:A method of cross-term removal for Wigner-Ville distribution is proposed to the detection of multi-component LFM signals.For the frequency characteristics of auto terms and cross terms,it removes cross terms by filtering WVD time-frequency matrix in the transform domain.The matrix transformation formula and the expression of all terms after transformation are given.And in view of the performance of filter,an energy weighted method is put forward to improve the slow oscillating cross term.Simulation and experimental results demonstrate that,it can eliminate the cross term with no reduction of time-frequency resolution.
摘要:Considering the features of carrier power line noise,a novel variable step-size adaptive interference cancellation algorithm is proposed in this paper.A new function relation formula between the varying step-size of adaptive algorithm and gradient is established.this algorithm not only make up for the deficiency of the variable step size algorithm based on the error in the adaptive interference cancellation,but also overcome the limitation of the standard LMS algorithm that its convergence is sensitive to the power of input signal.And the algorithm can adjust step size along with the gradient in order to converge faster.Also,theoretical analysis about the novel variable step-size adaptive interference cancellation algorithm is conducted in this paper,and the performance of the algorithm is verified by simulation and practical results.Simulation and practical results indicate the correctness of theoretical analysis and demonstrates the advantages of this algorithm.
摘要:3D spatial layout understanding from images plays an important role in the autonomous driving and object recognition.This paper proposes a 3D spatial layout understanding algorithm based on multiple CRFs.Firstly,multiple different scales super-pixel image are generated based on the multiple segmentation.Then,the feature of super-pixel are constructed based on LBP surface texture feature,orientation texture feature from LM filters,color feature,and location and shape feature of super-pixels in the image.Finally,the CRF model on every scale super-pixel image is built,the Dempster-Shafer theory of evidence is used to integrate the inference result of multiple CRF models and the 3D spatial layout understanding from an image is realized.The experiments on the public database Geometric Context and KITTI Layout demonstrate that the algorithm proposed in this paper improves the average accuracy of 3D spatial layout understanding comparing to the existing state-of-art.
关键词:3D spatial layout;multiple image segmentation;feature of super-pixel;conditional random field models;evidence combine
摘要:A novel nonlinear hyperspectral image unmixing algorithm based on differential search is proposed for solving the limitations of linear mixing model.The reconstruction error is used as the objective function for unmixing based on generalized bilinear model and the nonlinear unmixing is transformed into the optimization problem.The parameters in objective function are mapped onto the location variables of the search process and the differential search algorithm is used to optimize the objective function.In the optimization process,the constraint conditions for hyperspectral image unmixing are fulfilled by implementing the search range controlling strategy.And then,the abundance and the nonlinear parameters for unmixing can be obtained.Experiments on synthetic data and real data validate that the proposed nonlinear unmixing algorithm can effectively overcome the limitations of linear unmixing algorithm,as well as the local convergence of gradient optimization method,and the performance of the proposed algorithm is better than other state-of-the-art hyperspectral image unmixing algorithms.
摘要:An improved image dehazing algorithm based on dark channel prior is proposed to overcome the color distortion of sky and halo effects.The guided filter is utilized to segment the sky area finely to avoid the sky color distortion,since the defect of the classical dark channel prior theory.The global atmospheric light of image in sky region is estimated accurately.In addition,the detailed edge information can be got by taking advantage of median filter technique.So more effective transmission map estimation will be achieved which effectively inhibited the halo.Last,because the brightness of image after haze removal is lower than the actual scene,histogram equalization is used for channel V of the HSV color space.The experiment results show that.the proposed method can not only restore the clean scene from hazy images effectively,but also avoid color distortion of the sky region and halo artifacts.
摘要:In order to improve the sampling rate and the quality of the reconstructed images of electrical capacitance tomography (ECT) system,a new ECT image reconstruction algorithm based on compressed sensing theory was proposed.Firstly,using the orthogonal basis of Discrete Fourier Transformation,the gray signals of original images can be transformed into sparse signals.Then,14 electrodes randomly selected from the 16 electrodes ECT system were excited randomly and the capacitance values between different electrode pairs were also measured in a random order.By this way,the capacitance signals and the corresponding observation matrix were obtained.Finally,using L1 regularization model and primal dual interior point method,the gray signals of original images were achieved.The simulation results showed that the quality of the reconstructed images were better than the corresponding images obtained by the Landweber iterative algorithm.Therefore,the algorithm proposed can reconstruct high precision images with less observation data,which provides a new method for ECT image reconstruction.
关键词:electrical capacitance tomography;image reconstruction;compressed sensing;L1 regularization;primal dual interior point method
摘要:With the emerging of applications such as Social Network Services and biological information network analysis and the rapid development of computer technology,the scale of graph increases quickly and updates frequently,so the demand to deal with large scale dynamic graph becomes more pressing.The existing research works focusing on large scale dynamic graph are rare,which have shortcomings such as difficult index compression and needing optimizing graph structure.Therefore,in this paper,we present a reachability query processing method of dynamic large scale graph based on improved Huffman Coding,named Huffman-based Label Reachability,HuffLR.Firstly,the structure of pre-processing graph is compressed twice in order to gain the double compression graph.Secondly,the prefix-label index is constructed based on the double compression graph,which can express the reachability relations between nodes effectively.Lastly,we present the evolution of the double compression graph and reachability query processing and optimized algorithms,including insertion and deletion of edge,insertion and deletion of node.Experimental results demonstrate that the reachability query processing algorithm of dynamic large scale graph based on improved Huffman Coding has good feasibility and effectiveness.
关键词:reachability query;large scale graph;dynamic graph;Huffman coding;label index
摘要:Subgraph query is an important problem in the research of graph databases,and many methods about subgraph query are based on "filtering-verification strategy",which key target is to find effective feature patterns.Through the analysis of the embedding information of feature patterns in the data graphs,we propose to construct embedding relation indexing in the offline stage,and propose a new feature pattern embedding based subgraph query algorithm ERSearch.When query graph is given,we will use the co-occurrence relations and embedding relations combined to prune the unmatched data graphs,and the comparing results of embedded relationship in filtering phase can be used in the verification process,improving the efficiency of the verification.Via the experiment in the real and synthetic datasets,compared with PathIndex and other methods,we show that our algorithm can effectively reduce the size of candidate set,and effectively improve the efficiency of filtering and verification stages.
摘要:The rapid development of location based services set higher demands on efficiency promotion and cost control of the services.In the paper,we propose a k-nearest neighbor query algorithm based on density grid index.In processing of the algorithm,a series of candidate search radii is obtained by utilizing of the geometrical features of the rectangle.Then the appropriate candidate search radii are chosen to make distance filtering according to the density distribution of the moving object,it is useful to achieve reducing the unnecessary accessing to memory index units and disk index units.Our extensive experiments show that the efficiency of the density grid index with our algorithm is about equal to ST2B-tree on the k-nearest neighbor query,but our algorithm has obvious advantages in the cost of I/O.
摘要:It is still a very challenging issue to online track arbitrary targets in the unrestricted complex environment.This paper presents an online visual tracking method with improved collaborative appearance model based on model-free framework,solving the problem of most other tracking algorithms with collaborative model,which is unable to effectively select the positive and negative samples.According to the human visual perception rules,object edge information is regarded as the most discriminative feature,on which an edge discriminative appearance model is proposed.In order to remove background interference in likelihood matching space for generative model,a two-stage matching space is put forward via integrating dynamic model,detection module and edge discriminative model.The generative model based on partition strategy is constructed for space and appearance information.The final position and matching coefficient of each sub-block are calculated by mean-shift,as a basis for occlusion handling and model update.Experimental results using challenging public video sequences show the effectiveness and superiority of the proposed method,compared with other state-of-the-art visual tracking approaches.
摘要:There exist usually multiple faults in software systems.Mutual interference among them inhibits the ability of fault localization.A multiple fault localization based on Chameleon clustering was proposed.First,the suspiciousness of program elements is computed based on the combination of each failed program execution trace with all passed program execution traces.The most suspicious elements are selected as feature elements,which reduced the corresponding failed program execution traces.Second,the reduced failed program execution traces are performed by clustering analysis,after that,each failed cluster contains one fault.Third,each failed cluster merges passed cluster,and then the suspiciousness of program elements is computed.Finally,multiple faults are located simultaneously in terms of the descending suspiciousness of program elements in each failed cluster in parallel debugging mode.Experimental results show that the approach located multiple faults effectively.
摘要:Attribute reduction is one of important topics in rough set theory,and information entropy is an index of measuring the amount of information.After investigating absolute attribute reduct and several kinds of relatively attribute reducts,a general criterion of reducts is induced in rough set theory.With this criterion of reducts,attribute reduct based on information entropy and attribute reduct based on joint entropy are defined.The relationships among attribute reducts and absolute attribute reduct are investigated.Moreover,information loss based on information entropy for attribute reducts is defined,which can measure information loss after attribute reduction has been conducted.The old concepts that attribute reduction can not lose information are improved,and attribute reduction and classification can be further investigated from information loss and information entropy.
关键词:rough sets;attribute reduction;information entropy;joint entropy;information loss
摘要:An Improved Projection Twin Support Vector Machine (IPTSVM) is presented.The target of the proposed IPTSVM is to deal with a set of problems in the training and solving steps of PTSVM.We first propose a linear IPTSVM for binary classification.Then we extend it to the corresponding nonlinear version using kernel tricks.The paper has three main contributions to the community:(1) A new PTSVM-based method is proposed,in which we do not have to compute the inverse of a large matrix before the training step.(2) We design the nonlinear IPSVM that is obtained by using kernel tricks.(3) A new parameter is introduced,which can adjust the performance of the model and improve the classification accuracy of IPTSVM.Experimental results obtained from several datasets demonstrate that,compared with PTSVM,IPTSVM not only improves the classification accuracy but also overcomes some deficiencies to a certain extent.
关键词:support vector machine;nonparallel hyperplane support vector machine;projection twin support vector machine;pattern classification
摘要:The performance of spatial filter matrix degrades sharply in the presence of matrix dimension reduction.To solve the problem,a method using K-L (Karhunen-Loeve) Trans-form to reduce the matrix dimension is proposed.Theoretical derivation show the eigenvalues of the spatial-filter matrix and its conjugate transpose matrix product,has two characteristics.Firstly,there exists some eigenvalues that are much greater than the other eigenvalues.Secondly,the number of greater eigenvalues depends on the bandwidth of filter matrix pass-band.Based on those characteristics,K-L Trans-form was used to realize matrix dimension reduction through abandoning the eigenvectors corresponding to small eigenvalues.The proposed reduction dimension filter matrix has the advantage of orthogonality.Simulation results show the proposed reduction matrix and matrix with maximum dimension have similar filter capability.
摘要:A novel high order unscented transform (HUT) mechanism is proposed to improve the approximation accuracy of the nonlinear transformation.The HUT is adopted to select the Sigma points which can be used to approximate the posterior probability density of state variable by numerical integration.Thus the high order unscented Kalman filtering (HUKF) algorithm can be made up.Further,to solve the state estimation problem for nonlinear/non-Gaussian system,Gaussian sum high order unscented Kalman filter (GS-HUKF) is proposed by combining the HUKF and Gaussian sum filter (GSF).The basic idea of the GS-HUKF is that a cluster of Gaussian distribution is used to approximate the posterior probability density of state variable.At the mean time,each separated Gaussian distribution is estimated by HUKF.Numerical simulation results demonstrate that the proposed HUT has higher estimation precision than ordinary unscented transform (UT) method.The GS-HUKF has integrated advantages with respect to estimation accuracy and computational complexity and its performance is superior to the existing Gaussian sum filters.
关键词:Kalman filtering;unscented Kalman filter;Gaussian sum filter;nonlinear /non-Gaussian
摘要:From the real network attack-defense,aimed at the multi-stage and dynamic attack-defense process with the restriction of incomplete information,the multi-stage attack-defense signaling game model is proposed in the paper.Considering attenuation of the signal effect in the multi-stage attack and defense,signal attenuation factor is proposed for the quantification of attenuation.Based on the above,we design the solution for game equilibrium in multi-stage attack and defense.Then the algorithm of optimal active defense strategies selection is proposed.Finally,a simulation experiment is conducted to verify the effectiveness of the model and method proposed in the paper,through which some rules in the multi-stage attack-defense game are concluded.
关键词:network attack and defense;multi-stage signaling game;signaling attenuation;game equilibrium;defense strategies
摘要:For wireless sensor networks,traffic load of each node is changing with time and environment; adaptive inadequate also exists in traditional Carrier Sense Multi-channel Access (CSMA) protocol for channel access mechanisms.For these characteristics,under analyzes the shortcomings of the traditional CSMA protocols,to solve the problem of difficult to select the probabilities in the probabilistic CSMA protocol,the paper proposed the adaptive three-dimension probability CSMA (ATDP-CSMA) protocol based on adaptive mechanism,using the average cycle analysis method in the analysis of ATDP-CSMA protocol model,getting the precision expression of system throughput.Simulation results show that proposed protocol not only can be well adapted to the changes of the node traffic load but also can be maintained a relatively stable throughput even at a high load.
关键词:adaption;three-dimensional probability;carrier sense multi-channel access;throughput
摘要:A novel optional-iteration high speed and high precision CORDIC algorithm is proposed in this paper.First the rotation is conducted with a corresponding angle based on table-driven method.Then the algorithm bypasses unnecessary iterations using a new basic angle choosing technique.And the correction is achieved by shift and subtraction to reduce hardware consumption.Calculation and simulation indicate that the new algorithm can reduce the iteration number to less than 7 when the phase error is smaller than 10-5rad.In the application of DDFS,20 fractional binary bits design is implemented in Xilinx FPGA with range reduction method.This design can reduce amplitude error to smaller than 2×10-5 for sine and cosine,cut the output delay down to 43.5ns in circuit test,and no hardware consumption increase.
关键词:CORDIC(COrdinate rotation digital computer);DDFS(direct digital frequency synthesizer);table-driven;FPGA(Field Programmable Gate Array)
摘要:A delay-locked loop circuit of wide dynamic locking range and low static phase error is designed for Time to Digital Converter (TDC) application adopting dual delay lines,anti-lock control circuit structure and applying symmetrical matching techniques to key modules such as Charge Pump (CP),simultaneously.Simulation and Multi Project Wafer (MPW) tapeout are completed based on TSMC 0.35 μ m CMOS process.The test results show that DLL's frequency locking range is 40MHz-200MHz with its static phase error 161ps@125MHz.Driven by noise-free input clock,and operating on 200MHz,DLL's maximum peak-to-peak and root-mean-square jitters are 85.3ps and 9.44ps,respectively adapting the subnanosecond time-resolved TDC's application requirement.
摘要:In expensive multi-objective evolutionary algorithms,the evaluation of a large number of objective vectors spend a lot of time or experimental cost and lead to the cost of disaster.According to the fact that Pareto dominance relationships among candidate solutions are depended on the rank relationships of objective components,this paper proposes a predict method of rank equivalent to determine Pareto dominance.A decision vector and object vector rank matrix is established,and rank correlation analysis is used to calculate the correlation coefficient matrix R.Under the assumption of linear correlation,a prediction equation is established to predict rank relationships.Testing results on typical multi-objective optimization problems show that the proposed method only requires establishing a linear prediction model,which can remarkably improve the prediction accuracy and reduce the calculation of original expensive target function.Finally,the prediction method is integrated into the NSGA-II,it can avoid reconstruction the model in the process of evolution,then effectively decrease the number of evaluation for expensive objective vectors.
摘要:PRIDE is a light weight block cipher designed by Albrecht et al.in CRYPTO 2014,which adopts the classical SPN (Substitution Permutation Network) structure and iterates for 20 rounds.The construction of linear layers is very interesting and performances good both in security and efficiency.This paper investigates the properties of the S-boxes and the linear matrices,and then constructs 16 different 2-round iterative linear approximations with the bis 2-5 and 8 different 1-round iterative linear approximations with the bis 2-3.Base on some suitable approximations,attacks on 18-round and 19-round PRIDE are presented by means of linear cryptanalysis with the properties of key schedule,the linear characteristics and the partial-sum technique,which need about 274.9 encryptions with 260 known plaintexts and 274.9 encryptions with 262 known plaintexts,respectively.Furthermore,some interesting links between differential and linear characteristics are shown,which are helpful to reduce the compute complexity.Our analysis is the first linear attack on PRIDE block cipher with known plaintexts.
摘要:A large amount of achievements have been accumulated in steganalysis and steganography community for the past few decades.Nevertheless,the application of information hiding is restricted to research in laboratory,focusing on the confrontation between steganography and steganalysis,which has a huge distance from real world.Inspired by the cryptography,we establish a novel information hiding system whose algorithms are changeable and modification modes are under control based on investigation of previous work.We construct a huge multi-modal information hiding space with multiple algorithms and modification modes.Moreover,we build the mapping method between steganography methods and keys to implement the reconstruction mechanism of generating information hiding process when giving a key.There is no doubt that information hiding research scope will be expanded and vitality will be integrated.Experimental results and theoretic analysis have shown that the proposed system is effective and security.
关键词:information hiding;steganography;anti-forensic information hiding;multi-modal information hiding
摘要:Aiming at the handover authentication in the LTE-A,SDN is introduced and a new heterogeneous network framework named Software Defined LTE-A is proposed.This framework simplifies the handover authentication via the sharing of security context information in the Controllers.The use of Controller leads to one more communication overhead when the base station communicates to the core network.The standard handover authentication in LTE-A is a complex system that will generate a lot of communication overhead.The handover authentication based on proxy signature make the UE(User Equipment) need not to communicate to core network when UE is authenticated,which reduces the communication overhead.Compared to RSA Cryptography,the Elliptic Curve Cryptography needs less computation that will decrease the computation overhead in the Controller.Adopted the proxy signature based on the Elliptic Curve,a new handover authentication protocol is proposed,and is modeled,simulated,and analyzed by the Colored Petri Nets.The results of the simulation show that the proposed handover authentication is efficient and more secure.
关键词:LTE-A;handover authentication;SDN(software defined network);proxy signature based on elliptic curve;colored Petri Nets
摘要:Quantum radar as a new radar paradigm has been attracting much attention of researchers and institutions all over the world since proposed.This paper begins defining the scientific content of quantum radar from its technology characteristics;it presents the basic definition and classification of quantum radar and points out the advantages in the target detection performance compared with classical radar systems.Subsequently,viewing from the origin,development and actuality of quantum radar,the paper briefly introduces the history of quantum radar.In particular,the potential applications of quantum radar to radar target detection,measurement and imaging and the corresponding advantages are elaborated.Finally,by viewing the prospects for the development of quantum radar,several open problems in the implementation and application of quantum radar are proposed.
摘要:In order to improve the recognition performance of premature ventricular contraction (PVC),this paper reports an algorithm based on ensemble learning.First,the tow-lead ECG signals from the MIT-BIH Arrhythmia database are classified into PVC and non PVC beats using lead convolutional neural network (LCNN) classifier.Then the results are fused with some rules.The accuracy,sensitivity and specificity of the proposed algorithm are 99.91%,98.76% and 99.97%,respectively,which are better than that of other existing algorithms for PVC beats classification.In addition,this paper realizes an inter-patient PVC recognition experiment by combining LCNN and diagnostic rules for clinical application.The effectiveness of the proposed algorithm has been confirmed by the accuracy (97.87%),sensitivity (87.94%) and specificity (98.02%) with the data set over 140000 ECG records.
摘要:A novel error amplifier with integration of multi-functions for peak-current mode DC-DC converters is presented.Soft-start is achieved by the error amplifier combined with a ramp voltage signal.A smooth transition from start-mode to the steady state is achieved without disturbance,and the inrush current and the overshoot of the output voltage during start-up are eliminated effectively.Moreover,this novel error amplifier has other two functions,which are the maximum current limit and working mode switching.The error amplifier is applied to a peak-current mode BOOST DC-DC converter that is implemented with CSMC 0.5 μ m BCD process.Simulation results show that the static current consumption of the error amplifier is 4.48 μ A with 3.5V supply voltage,and the soft-start,maximum current limit and working mode switching functions are achieved by the multi-functions error amplifier.The presented circuit is concise and simple to implement,and has features of low power.
关键词:error amplifier;DC-DC converter;current mode;soft-start;low power