14995264
A mixed-signal simulator for VHDL-AMS
25955132
A new synchronization algorithm for VHDL-AMS simulation
VHDL-AMS is the Analog and Mixed-Signal Extensions to VHDL. The paper gives a brief overview of the added features to VHDL. A mixed-signal simulator has been developed based on VHDL-AMS. A new synchronization algorithm is adopted in the simulator. Using the new algorithm the analog kernel does not need to synchronize the digital kernel at each digital event time point. The efficiency of the new synchronization algorithm is tested by examples. Simulation results show the newly developed algorithm can speed up the simulation.
35611392
CLUCGS and CLUCR - two matrix solution methods for general circuit simulation
Direct methods and iterative methods have been used in most analog circuit analysis tools for matrix solution. But neither can efficiently solve the large-scale sparse matrix or ill matrix because of the closely coupled relationship of execution time and matrix size for direct methods and the convergence problem for iterative methods. This paper presents two methods that are a combination of direct solution using complete LU factorization and iterative solution using conjugate gradient square (CGS) or conjugate residual (CR) method. The methods converge faster and more reliably than the LU factorization method and conjugate gradient (CG) method, and can achieve high resolution on a wide variety of circuits. A very efficient preconditioning method is used in our approach to accelerate convergence. Furthermore, we present an effective judgment method for re-factorization of matrix. Several numerical experiments results are included to compare their efficiencies.
43513684
A representation theorem for recovering contraction relations satisfying wci
A notion of an image structure associated with the canonical epistemic state is introduced. Based on it, we get a representation result for recovering contraction inference relations satisfying the condition weak conjunctive inclusion (wci) in terms of F-standard epistemic AGM states. In effect, this result establishes a representation theorem for belief contraction functions satisfying AGM postulates (k-1) - (k-7), and Rott's (wci) and (k-8c), and hence generalizes Rott's corresponding result in the finite framework.
6852082
Multi-strategy ensemble particle swarm optimization for dynamic optimization
Optimization in dynamic environments is important in real-world applications, which requires the optimization algorithms to be able to find and track the changing optimum efficiently over time. Among various algorithms for dynamic optimization, particle swarm optimization algorithms (PSOs) are attracting more and more attentions in recent years, due to their ability of keeping good balance between convergence and diversity maintenance. To tackle the challenges of dynamic optimization, several strategies have been proposed to enhance the performance of PSO, and have gained success on various dynamic optimization problems. But there still exist some issues in dynamic optimization which need to be studied carefully, i.e. the robustness of the algorithm to problems of various dynamic features. In this paper, a new multi-strategy ensemble particle swarm optimization (MEPSO) for dynamic optimization is proposed. In MEPSO, all particles are divided into two parts, denoted as part I and part II, respectively. Two new strategies, Gaussian local search and differential mutation, are introduced into these two parts, respectively. Experimental analyses reveal that the mechanisms used in part I can enhance the convergence ability of the algorithm, while mechanisms used in part II can extend the searching area of the particle population to avoid being trapped into the local optimum, and can enhance the ability of catching up with the changing optimum in dynamic environments. The whole algorithm has few parameters that need to be tuned, and all of them are not sensitive to problems. We compared MEPSO with other PSOs, including MQSO, PHPSO and Standard PSO with re-initialization, on moving peaks Benchmark and dynamic Rastrigin function. The experimental results show that MEPSO has pretty good performance on almost all testing problems adopted in this paper, and outperforms other algorithms when the dynamic environment is unimodal and changes severely, or has a great number of local optima as dynamic Rastrigin function does.
206544153
Analysis of creeping locomotion of a snake robot on a slope
Biological snakes' diverse locomotion modes and physiology make them supremely adapted for environment. To realize these snakes' noticeable features, we have developed a snake-like robot that has no any forward direction driving force. To enlarge the environment-adaptable ability of our robot, in this study we discuss the creeping locomotion of our snake-like robot on a slope. A computer simulator is presented for analysis of the creeping locomotion of our snake-like robot on a slope, and the environment-adaptable body shape for the creeping locomotion of the snake-like robot on slope is also derived through this simulator.
13764046
A Parallel and Distributed Method for Computing High Dimensional MOLAP
Data cube has been playing an essential role in fast OLAP(on-line analytical processing) in many multidimensional data warehouse. We often execute range queries on aggregate cube computed by pre-aggregate technique in MOLAP. For the cube with d dimensions, it can generate 2d cuboids. But in a high-dimensional data warehouse (such as the applications of bioinformatics and statistical analysis, etc.), we build all these cuboids and their indices and full materialized the data cube impossibly. In this paper, we propose a multi-dimensional hierarchical fragmentation of the fact table based on dimension hierarchical encoding. This method partition the high dimensional data cube into shell mini-cubes. Using dimension hierarchical encoding and pre-aggregated results, OLAP queries are computed online by dynamically constructing cuboids from the fragment data cubes. Such an approach permits a significant reduction of processing and I/O overhead for many queries by restricting the number of fragments to be processed for both the fact table and bitmap encoding data. This method also supports parallel I/O and parallel processing as well as load balancing for disks and processors. We have compared the methods of our parallel method with the other existed ones such as partial cube by experiment. The analytical and experimental results show that the method of our parallel method proposed in this paper is more efficient than the other existed ones.
483866
3D Locomotion of a Snake-like Robot Controlled by Cyclic Inhibitory CPG Model
With 3D (3-dimensional) movement's ability and rhythmic locomotion mode, a nature snake makes itself survive in rugged terrains. The rhythmic activities of most creatures are generated by the CPG (central pattern generator). Based on this fact, the sustained-type neuron has been adopted to construct a cyclic inhibitory CPG model for a snake-like robot whose joints are perpendicularly connected in series. Having compared with the sustained-type neuron and the mutual inhibitory CPG, the cyclic inhibitory CPG was proven to generate capably rhythmic output with the least number of differential equations. In this paper, we introduce the neuron network organized by the cyclic inhibitory CPGs connected in line with unilateral excitation to control the 3D locomotion of a snake-like robot, and present the necessary condition for the CPG neuron network to sustain a rhythmic output. By implementing this control architecture to a simulator with consideration of mechanical dynamics of a real snake-like robot "Perambulator", preliminary parameter setting of the CPG neuron network for its 3D locomotion is obtained. Moreover, it is shown that "Perambulator" can successfully exhibit 3D locomotion by using the output of the proposed CPG network. The obtained results have also provided a bran new approach to understand the unknown neuron network of nature snakes