This paper presents the application of the Self-Adaptive Evolutionary programming optimization technique in the Power System State Estimation problem. State Estimation is a statistical-based optimization process used ...
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This paper presents the application of the Self-Adaptive Evolutionary programming optimization technique in the Power System State Estimation problem. State Estimation is a statistical-based optimization process used in power systems to obtain the complex bus voltages of the system under study. The number of decision variables in the State Estimation problem grows in proportion to the size of the power system being considered. Therefore, it would be desirable to have robust state estimation procedures, with the ability to overcome premature stagnation or convergence problems. The Self-Adaptive Evolutionary programming method is an enhanced version of the canonical Evolutionary programming algorithm, which has been used successfully for solving high-dimensional continuous optimization problems. In order to validate the effectiveness of the proposed method, two case studies were considered. In the first one, the State Estimation problem was stated according with the Weighted Least Squares formulation and the results obtained on a 6-bus system were compared to those obtained via Newton's method. In the second case study, which was based on a 30-bus system, the results given by the Weighed Least Squares and Weighed Least Absolute Value formulations were compared to each other. The results from both case studies demonstrate the applicability of the proposed method for State Estimation purposes.
This paper presents a new algorithm for finding the point of correspondence in stereo images using a Hopfield Neural Network (HNN). A 2D HNN is used to match primitives extracted form one image to the other. The featu...
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This paper presents a new algorithm for finding the point of correspondence in stereo images using a Hopfield Neural Network (HNN). A 2D HNN is used to match primitives extracted form one image to the other. The features used for this operation are edge points extracted using the Sobel operator. A formulation of the stereo correspondence as an optimization problem has been presented where various geometrical properties of multiple view geometry including Disparity Gradient (DG) have been used as constraints on the objective function. The 2D HNN is then used to minimize this function, thus achieving an optimum correspondence from one to the other image. The results show higher accuracy than template matching and local search methods.
A method for designing FIR digital filters, with each coefficient a sum of signed power-of-2 terms, by sphere relaxation is proposed. To justify the design methodology, we present an analysis showing that the globally...
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A method for designing FIR digital filters, with each coefficient a sum of signed power-of-2 terms, by sphere relaxation is proposed. To justify the design methodology, we present an analysis showing that the globally optimal design always lies in a vicinity of the optimal FIR filter with continuous coefficients. The design problem at hand is then addressed using a new relaxation method in which the constraints characterizing the binary nature of the design variables are relaxed to a single sphere type constraint on the corresponding continuous variables. This yields a simple nonconvex continuous optimization problem whose solution can be calculated considerably faster than previously reported relaxation methods. Design examples are presented to demonstrate that the proposed algorithm offers near-optimal designs with small fraction of design complexity relative to that required by the existing methods
Computing the maximal output of a linear time-invariant (LTI) system is an important part of the design of critical systems. We compare three numerical methods for computing the maximal output of an LTI system subject...
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Computing the maximal output of a linear time-invariant (LTI) system is an important part of the design of critical systems. We compare three numerical methods for computing the maximal output of an LTI system subject to inputs with limited magnitude and rate of change. The three methods are: (1) quadratic programming method, (2) convex optimisation method, and (3) upper bound method. Two numerical examples are given to examine the three methods in terms of accuracy, efficiency, and conservativeness. We show that the quadratic programming method is superior to the other two methods from the viewpoint of accuracy and efficiency of computing the theoretically maximal output, while only the convex optimisation method has the capability to allow for the input's frequency range, which leads to good estimation of the practically maximal output and less conservative control system design. We also issue a guideline for selecting the order of Fourier series expansion required in the convex optimisation method
Establishing suitable programming models for pervasive spaces is essential in improving the productivity, enhancing the quality of pervasive systems, and creating an open platform for interoperability. Two different m...
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Establishing suitable programming models for pervasive spaces is essential in improving the productivity, enhancing the quality of pervasive systems, and creating an open platform for interoperability. Two different models, namely, the context-driven model and the service-oriented model, have been proposed and studied for their feasibilities as the foundation for implementing programmable pervasive spaces. We present these two alternatives and contrast their advantages and disadvantages.
Functional validation is a major bottleneck in hardware design. Two main approaches to ensure functional correctness of hardware systems are based on formal verification and simulation techniques. It is widely recogni...
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Functional validation is a major bottleneck in hardware design. Two main approaches to ensure functional correctness of hardware systems are based on formal verification and simulation techniques. It is widely recognized that formal verification techniques are exhaustive but do not scale well; simulation-based techniques are scalable but are not exhaustive. Possible compromise is provided by semi-formal approaches combining formal specifications, functional coverage definition, and simulation. This paper describes the UniTESK approach to specification-based validation of hardware designs in which a good balance of exhaustiveness and scalability is found. UniTESK is originally intended for the development of high-quality functional tests for software systems. The paper shows how to adapt it for functional validation of Verilog HDL and SystemC designs.
We present a framework for synthesizing low-power nested transconductance (G m )-capacitance compensation (NGCC) amplifiers through global optimization over generally nonconvex polynomials. Specifically, a nonconvex o...
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We present a framework for synthesizing low-power nested transconductance (G m )-capacitance compensation (NGCC) amplifiers through global optimization over generally nonconvex polynomials. Specifically, a nonconvex optimization problem is formulated, which is then efficiently solved through convex programming techniques based on linear matrix inequality (LMI) relaxation. Such framework allows both polynomial inequality and equality constraints, thereby facilitating more accurate transistor modelings. Compared to conventional nonlinear programming (NLP) approach such as genetic algorithm (GA), the proposed methodology exhibits superior computational efficiency, and guarantees convergence to globally optimal parameters. To demonstrate the design flow, a NGCC amplifier is designed with 0.35 mum technology and contrasted against HSPICE simulations
As we approach the limits of CMOS technology, novel multiprocessor architectures are the industry's best shot to keep up with the expectations of the consumer electronics market regarding functionality and perform...
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As we approach the limits of CMOS technology, novel multiprocessor architectures are the industry's best shot to keep up with the expectations of the consumer electronics market regarding functionality and performance improvements. While many advances were achieved on efficient concurrent usage of the multiprocessing architectural features, the capturing and exploration of concurrency at the application level is still an open question. This paper will provide an outlook on different concepts and techniques available in modeling frameworks like UML, Matlab/Simulink and Ptolemy II, as well as the features and limitations from concurrent programming and hardware description languages. It will provide details on the most relevant of them and will identify the most likely candidates to be integrated into the design flow that will be used by SoC designers and application developers in the next five to ten years
A new framework is presented for sensor network programming with situations. User requirements are expressed in terms of temporal and spatial constraints on the events observed by sensor network nodes. A novel spatial...
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A new framework is presented for sensor network programming with situations. User requirements are expressed in terms of temporal and spatial constraints on the events observed by sensor network nodes. A novel spatial-temporal logic is introduced for this task. We also specify protocols for situation detection that can be executed on sensor nodes to meet those requirements. The feasibility of situation-based sensor network programming using our framework is illustrated by two examples: a temporal situation for recognising the occurrence of an explosion, and a spatial situation for detecting contours in a sensor node field.
A computer aided design method for linear multirate digital control systems is presented in this paper. The design problem is formulated on the infinity norm of signals and the induced l 1 -system norm. An upper bound...
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A computer aided design method for linear multirate digital control systems is presented in this paper. The design problem is formulated on the infinity norm of signals and the induced l 1 -system norm. An upper bound for the l 1 -system norm leading to matrix inequalities is the basis of the design procedure. It is a characteristic feature of the method that the controller is attained by repeatedly solving small size convex optimization problems. Considering an example it turns out, that multirate digital controllers can help to overcome the well known problem of inflating controller order in induced l 1 -control
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