采样系统的提升技术:是与非?

The lifting technique is now a well recognized tool for H1 design and analysis of sampled-data systems. However, the efficiency of the method depends on the structure of the problem. The structure of the H1 sensitivity problem is analyzed in this paper. And the constraints on the H1-optimization problem and on the design parameters in lifting design are also discussed. Under such constraints the resulting performance from the design is generally low. Therefore, the lifting technique can not be recommended as a synthesis tool for the sampled-data systems. An example is also given in the paper.     

The Lifting Technique for Sampled-data Systems:Useful or Useless?

The lifting technique is now a well recognized tool for H_∞design and analysis of sampled- data systems.However,the efficiency of the method depends on the structure of the problem.The structure of the H_∞sensitivity problem is analyzed in this paper.And the constraints on the H_∞-optimization problem and on the design parameters in lifting design are also discussed.Under such constraints the resulting performance from the design is generally low.Therefore,the lifting technique can not be recommended as a synthesis tool for the sampled-data systems.An example is also given in the paper.     

Word Spotting Based on a posterior Measur of Keyword Confidence

In this paper,an approach of keyword confidence estimation is developed that ewll combines acoustic layer scores and syllable-based statistical language model(LM)scores.An a posterioir(AP)confidence measure and its forward-backward calculating algorithm are deduced.A zero false alarm(ZFA) assumption is proposed for evaluating relative confidence measures by word spotting task.In a word spotting experiment with a vocabulary of 240 keywords,the keyword accuracy under the AP measure is above 94%,which well approaches its theoretical upper limit.In addition,a syllable lattice Hidden Markov Model(SLHMM) is formulated and a unified view of confidence estimation.word spotting,optimal path search,and N-best syllable re-scoring is presented ,The proposed AP measure can be easily applied to various speech recognition systems as well.     

Discrete-time dynamic graphical games: model-free reinforcement learning solution

This paper introduces a model-free reinforcement learning technique that is used to solve a class of dynamic games known as dynamic graphical games. The graphical game results from multi-agent dynamical systems, where pinning control is used to make all the agents synchronize to the state of a command generator or a leader agent. Novel coupled Bellman equations and Hamiltonian functions are developed for the dynamic graphical games. The Hamiltonian mechanics are used to derive the necessary conditions for optimality. The solution for the dynamic graphical game is given in terms of the solution to a set of coupled Hamilton-Jacobi-Bellman equations developed herein. Nash equilibrium solution for the graphical game is given in terms of the solution to the underlying coupled Hamilton-Jacobi-Bellman equations. An online model-free policy iteration algorithm is developed to learn the Nash solution for the dynamic graphical game. This algorithm does not require any knowledge of the agents’ dynamics. A proof of convergence for this multi-agent learning algorithm is given under mild assumption about the inter-connectivity properties of the graph. A gradient descent technique with critic network structures is used to implement the policy iteration algorithm to solve the graphical game online in real-time.     

A General Approach for Dexterous Manipulation Planning Based on Configuration Space Structuring

In this paper, we propose a new method for the dexterous manipulation planning problem, under quasi-static movement assumption. This method computes both object and finger trajectories as well as finger relocation sequence and applies to every object shape and hand geometry. It relies on the exploration of the particular subspaces GS k that are the subspaces of all the grasps that can be achieved for a given set of k grasping fingers. The originality is to use continuous paths in these subspaces to directly link two configurations. The proposed approach captures the GS k connectivity in a graph structure. The answer of the manipulation planning query is then given by searching a path in the computed graph. Another specificity of our technique is that it considers manipulated object and hand as an only system, unlike most existing methods that first compute object trajectory then fingers trajectories and thus can not find a solution in all situations. Simulation experiments were conducted for different dexterous manipulation task examples to validate the proposed method.     

Generic regular decompositions for generic zero-dimensional systems

Two new concepts,generic regular decomposition and regular-decomposition-unstable(RDU)variety for generic zero-dimensional systems,are introduced in this paper and an algorithm is proposed for computing a generic regular decomposition and the associated RDU variety of a given generic zero-dimensional system simultaneously.The solutions of the given system can be expressed by finitely many zero-dimensional regular chains if the parameter value is not on the RDU variety.The so called weakly relatively simplicial decomposition plays a crucial role in the algorithm,which is based on the theories of subresultants.Furthermore,the algorithm can be naturally adopted to compute a non-redundant Wu’s decomposition and the decomposition is stable at any parameter value that is not on the RDU variety.The algorithm has been implemented with Maple 16 and experimented with a number of benchmarks from the literature.Empirical results are also presented to show the good performance of the algorithm.     

A semantics-based approach for achieving self fault-tolerance of protocols

The cooperation of different processes may be lost by mistake when a protocol is executed.The protocol cannot be normally operated under this condition.In this paper,the self fault-tolerance of protocols is discussed,and a semanticslbased approach for achieving self fault-tolerance of protocols is presented.Some main characteristics of self fault-tolerance of protocols concerning liveness,nontermination and infinity are also presented.Meanwhile,the sufficient and necessary conditions for achieving self fault-tolerance of protocols are given.Finally,a typical protocol that does not satisfy the self fault-tolerance is investigated,and a new redesign version of this existing protocol using the proposed approach is given.     

Speech Detection in Non-Stationary Noise Based on the 1/f Process

In this paper,an effective and robust active speech detection method is proposed based on the 1/f process technique for signals under non-stationary noisy environments.The Gaussian 1/f process ,a mathematical model for statistically self-similar radom processes based on fractals,is selected to model the speech and the background noise.An optimal Bayesian two-class classifier is developed to discriminate them by their 1/f wavelet coefficients with Karhunen-Loeve-type properties.Multiple templates are trained for the speech signal,and the parameters of the background noise can be dynamically adapted in runtime to model the variation of both the speech and the noise.In our experiments,a 10-minute long speech with different types of noises ranging from 20dB to 5dB is tested using this new detection method.A high performance with over 90% detection accuracy is achieved when average SNR is about 10dB.     

CLASCN:Candidate Network Selection for Efficient Top-k Keyword Queries over Databases

Keyword Search Over Relational Databases (KSORD) enables casual or Web users easily access databases through free-form keyword queries. Improving the performance of KSORD systems is a critical issue in this area. In this paper, a new approach CLASCN (Classification, Learning And Selection of Candidate Network) is developed to efficiently perform top-fc keyword queries in schema-graph-based online KSORD systems. In this approach, the Candidate Networks (CNs) from trained keyword queries or executed user queries are classified and stored in the databases, and top-fc results from the CNs are learned for constructing CN Language Models (CNLMs). The CNLMs are used to compute the similarity scores between a new user query and the CNs from the query. The CNs with relatively large similarity score, which are the most promising ones to produce top-fc results, will be selected and performed. Currently, CLASCN is only applicable for past queries and New All-keyword-Used (NAU) queries which are frequently submitted queries. Extensive experiments also show the efficiency and effectiveness of our CLASCN approach.     

The Modelling of Temporal Data in the Relational Database Environment

This research takes the view that the modelling of temporal data is a fundamental step towards the solution of capturing semantics of time.The problems inherent in the modelling of time are not unique to database processing.The representation of temporal knowledge and temporal reasoning arises in a wide range of other disciplines.In this paper an account is given of a technique for modelling the semantics of temporal data and its associated normalization method.It discusses the techniques of processing temporal data by employing a Time Sequence (TS) data model.It shows a number of different strategies which are used to classify different data properties of temporal data,and it goes on to develop the model of temporal data and addresses issues of temporal data application design by introducing the concept of temporal data normalisation.     

CLASCN： Candidate Network Selection for Efficient Top-κ Keyword Queries over Databases

Keyword Search Over Relational Databases （KSORD） enables casual or Web users easily access databases through free-form keyword queries. Improving the performance of KSORD systems is a critical issue in this area. In this paper, a new approach CLASCN （Classification, Learning And Selection of Candidate Network） is developed to efficiently perform top-κ keyword queries in schema-graph-based online KSORD systems. In this approach, the Candidate Networks （CNs） from trained keyword queries or executed user queries are classified and stored in the databases, and top-κ results from the CNs are learned for constructing CN Language Models （CNLMs）. The CNLMs are used to compute the similarity scores between a new user query and the CNs from the query. The CNs with relatively large similarity score, which are the most promising ones to produce top-κ results, will be selected and performed. Currently, CLASCN is only applicable for past queries and New All-keyword-Used （NAU） queries which are frequently submitted queries. Extensive experiments also show the efficiency and effectiveness of our CLASCN approach.     

Linear quadratic regulation for discrete-time systems with state delays and multiplicative noise

In this paper, the linear quadratic regulation problem for discrete-time systems with state delays and multiplicative noise is considered. The necessary and sufficient condition for the problem admitting a unique solution is given. Under this condition, the optimal feedback control and the optimal cost are presented via a set of coupled difference equations. Our approach is based on the maximum principle. The key technique is to establish relations between the costate and the state.     

Management of Statically Modifiable Prolog Code

The Warren Abstract Machine is an efficient execution model for Prolog,which has become the basis of many high performance Prolog systems.However.little support for the implementation of the non-logical components of Prolog is provided in the WAM.The original Warren code is not modifiable.In this paper,we show how static modifications of Warren code can be achieved by adding a few instructions and a little extra information to the code.The implementation of the code manager is discussed.Algorithms for some basic operations are given.     

Improved method to generate path-wise test data

Gupta et al.,propsed a method ,which is referred to as the Iterative Relaxation Method ,to generate test data for a given path in a program by linearizing the predicate functions.In this paper,a model language is presented and the properties of static and dynamic data depen-dencies are investigated ,The notions in the Interative Relaxation Method are defined formally.The predicate slice proposed by Gupta et al.is extended to path-wise static slice.The correctness of the constructional algorithm is proved afterward The improvement shows that the constructions of predicate slice and input dependency set can be omitted .The equivalence of systems of constraints generated by both methods is proved ,The prototype of path-wise test data generator is presented in this paper,The experiments show shat our method is practical ,and fits the path-wise automatic generation of test data for both whicte -bos testing and black-blx testing.     

Observability conditions of switched linear singular systems

The observability problem of switched linear singular(SLS) systems is studied in this paper. Based on the observability definition, the unobservable subspaces of given switching laws are investigated under the condition that all subsystems are regular. A necessary condition and a sufficient condition for observability of SLS systems are given. It is shown that the observability and controllability are dual for some special SLS systems with circulatory switching laws. The method developed here is applicable to the observability analysis of normal switched linear systems.     

Hardware-Software Collaborative Techniques for Runtime Profiling and Phase Transition Detection

Dynamic optimization relies on runtime profile information to improve the performance of program execution. Traditional profiling techniques incur significant overhead and are not suitable for dynamic optimization. In this paper, a new profiling technique is proposed, that incorporates the strength of both software and hardware to achieve near-zero overhead profiling. The compiler passes profiling requests as a few bits of information in branch instructions to the hardware, and the processor executes profiling operations asynchronously in available free slots or on dedicated hardware. The compiler instrumentation of this technique is implemented using an Itanium research compiler. The result shows that the accurate block profiling incurs very little overhead to the user program in terms of the program scheduling cycles. For example, the average overhead is 0.6% for the SPECint95 benchmarks. The hardware support required for the new profiling is practical. The technique is extended to collect edge profiles for continuous phase transition detection. It is believed that the hardware-software collaborative scheme will enable many profile-driven dynamic optimizations for EPIC processors such as the Itanium processors.     

Towards robustness to speech rate in mandarin all-syllable recognition

In mandarin all-syllable recognition,many insert errors occur due to the influence of non-consonant syllables.Introducing the duration model into the recognition process is a direct way to lessen these errors.But that usually could not work well as expected,for the duration is sensitive to speech rate.Hence,aiming at this problem,a novel context dependent duration distribution normalized by speech rate is proposed in this paper and applied to a speech recognition system based on the frame of improved Hidden Markov Model (HMM).To realize this algorithm,the authors employ a new method to estimate the speech rate of a sentence; then compute the duration probability combined with speech rate;and finally implement this duration information in the post-processing stage.With little change in the recognition process and resource demand,the duration model is adopted efficiently in the system.The experimental results indicate that the syllable error rates decrease significantly in two different speech corpora.Especially for the insertions,the error rates reduce about sixty to eighty percent.     

Constructing Isosurfaces from 3D Data Sets Taking Account of Depth Sorting of Polyhedra

Creating and rendering intermediate geometric primitives is one of the approaches to visualisze data sets in 3D space.Some algorithms have been developed to construct isosurface from uniformly distributed 3D data sets.These algorithms assume that the function value varies linearly along edges of each cell.But to irregular 3D data sets,this assumption is inapplicable.Moreover,the detth sorting of cells is more complicated for irregular data sets,which is indispensable for generating isosurface images or semitransparent isosurface images,if Z-buffer method is not adopted.In this paper,isosurface models based on the assumption that the function value has nonlinear distribution within a tetrahedron are proposed.The depth sorting algorithm and data structures are developed for the irregular data sets in which cells may be subdivided into tetrahedra.The implementation issues of this algorithm are discussed and experimental results are shown to illustrate potentials of this technique.     

LBMBS： A Load-Balanced Moveable Bubble Scheme for Tori Interconnection Networks

Moveable bubble flow control is an efficient technique to avoid deadlock for torus networks. However, it does not take into consideration the load balance feature. Therefore, this leads to inefficient resources utilization. Moreover, packets may be discarded due to the congestion of a network area. On the other hand, there are other algorithms that consider load balancing such as rHALB （r hop adaptive load-balanced）routing technique. Nonetheless, rHALB detects deadlock using the timeout threshold. This concept of deadlock detection may give incorrect responses in case the traffic is high. Therefore, packets are dropped although there is no deadlock. At the end, this affects the whole performance of the network. This paper proposes a new routing algorithm for tori interconnection networks, namely, the LBMBS （load-balanced moveable bubble scheme）. LBMBS integrates both concepts of moveable bubble and rHALB in order to provide at the end a load-balanced efficient deadlock-free algorithm. The protocol details are given and compared against other routing algorithms in the literature.     

A Fault—Tolerant File Management Algorithm in Distributed Computer System “THUDS”

A concurrent control with independent processes from simultaneous access to a critical section is discussed for the case where there are two distinct classes of processes known as readers and writers.The readers can share the file with one another,but the interleaved execution with readers and writers may produce undesirable conflicts.The file management algorithm proposed in this paper is the activity of avoiding these results.This algorithm not only guarantees the consistency and integrity of the shared file,but also supports optimal parallelism.The concept of dynamic virtual queue is introduced and serves the foundation for this algorithm.Our algorithm with its implicit redundancy allows software fault-tolerant technique.