The conjugate gradient fast Fourier-Hankel transforms (CG-FFHT) method was recently proposed to solve the problems of electromagnetic wave propagation and scattering in axisymmetric inhomogeneous media. This new techn...
详细信息
The conjugate gradient fast Fourier-Hankel transforms (CG-FFHT) method was recently proposed to solve the problems of electromagnetic wave propagation and scattering in axisymmetric inhomogeneous media. This new technique uses the CG method together with the FFHT to solve the wave equation iteratively. Each iteration of the CG method requires O(N log2 N) complex multiplications (N is the number of unknowns). For the application of low-frequency induction logging, the number of iterations is very small (less than eight). Furthermore, the CG-FFHT method only requires the storage of several vectors of dimension N. In this paper we present an improved fast Hankel transform (FHT) algorithm as well as some applications of the CG-FFHT method. It is shown that the improved FHT algorithm results in better accuracy and is more efficient than the other FHT algorithms. Moreover, with this FHT algorithm there is ho need to pad the function to be transformed with zeros. Several numerical examples will be shown to illustrate the use of the improved FHT algorithm as well as the applications of the CG-FFHT method.
In this study, we propose and develop a Machine Learning-based metasolver for the Multi-Agent Path Finding (MAPF) problem, with the aim of selecting the most suitable solver based on the specific characteristics of th...
详细信息
In this study, we propose and develop a Machine Learning-based metasolver for the Multi-Agent Path Finding (MAPF) problem, with the aim of selecting the most suitable solver based on the specific characteristics of the problem and a user-provided time constraint. The approach aims to improve the performance of the best-performing solver on average and approximate the performance of a perfect selector. To achieve this, a comprehensive and diverse dataset was compiled, and state-of-the-art algorithms were selected and modified to efficiently handle the time constraint. Also, relevant features were identified, and a precise and robust Machine Learning model was constructed using the XGBoost algorithm. The model was evaluated and compared against other state-of-the-art methods. The results demonstrate that the proposed approach is effective and consistent, outperforming the Single Best Solver and approximating the performance of the Virtual Best Solver.
A novel finite difference beam propagation method (BPM) analysis based upon a bi-oblique coordinate representation is presented. The analysis yields a computationally efficient algorithm that permits accurate simulati...
详细信息
A novel finite difference beam propagation method (BPM) analysis based upon a bi-oblique coordinate representation is presented. The analysis yields a computationally efficient algorithm that permits accurate simulation of a wide variety of structures to be made without staircase approximations. Further, the independent paraxial and wide angle approximations, centered upon the direction of optical field propagation in each branching waveguide, may be incorporated into the algorithm. This feature allows a low-order approximation to be used in the algorithm even if one or both of the branching angles is large. The approach has been applied to both symmetric and asymmetric optical waveguide Y-junctions and produces results in excellent agreement with those in the literature.
Several issues related to vector quantization for noisy channels are discussed. An algorithm based on simulated annealing is developed for assigning binary codewords to the vector quantizer code-vectors. It is shown t...
详细信息
Several issues related to vector quantization for noisy channels are discussed. An algorithm based on simulated annealing is developed for assigning binary codewords to the vector quantizer code-vectors. It is shown that this algorithm could result in dramatic performance improvements as compared to randomly selected codewords. A modification of the simulated annealing algorithm for binary codeword assignment is developed for the case where the bits in the codeword are subjected to unequal error probabilities (resulting from unequal levels of error protection). An algorithm for the design of an optimal vector quantizer for a noisy channel is briefly discussed, and its robustness under channel mismatch conditions is studied. Numerical results for a stationary first-order Gauss-Markov source and a binary symmetric channel are provided. It is concluded that the channel-optimized vector quantizer designalgorithm, if used carefully, can result in a fairly robust system with no additional delay. The case in which the communication channel is nonstationary (as in mobile radio channels) is studied, and some preliminary ideas for quantizer design are presented.< >
ln this note, we present a strongly code disjoint (SCD) built-in current sensor (BICS) based on self-exercising concept. The integration of this SCD BICS with a self-checking circuit achieves the totally self-checking...
详细信息
ln this note, we present a strongly code disjoint (SCD) built-in current sensor (BICS) based on self-exercising concept. The integration of this SCD BICS with a self-checking circuit achieves the totally self-checking goal in static CMOS realizations, even in the presence of stuck-on and bridging faults, and results In a strongly fault-secure realization. Low-cost and high fault coverage is attractive for many high reliability and critical applications.
Mobile wireless sensor networks have been extensively deployed for enhancing environmental monitoring and surveillance. The availability of low-cost mobile robots equipped with a variety of sensors makes them promisin...
详细信息
Mobile wireless sensor networks have been extensively deployed for enhancing environmental monitoring and surveillance. The availability of low-cost mobile robots equipped with a variety of sensors makes them promising in target coverage tasks. They are particularly suitable where quick, inexpensive, or nonlasting visual sensing solutions are required. In this paper, we consider the problem of low complexity target tracking to cover and follow moving targets using flying robots. We tackle this problem by clustering targets while estimating the camera location and orientation for each cluster separately through a cover-set coverage method. We also leverage partial knowledge of target mobility to enhance the efficiency of our proposed algorithms. Three computationally efficient approaches are developed: predictive fuzzy, predictive incremental fuzzy, and local incremental fuzzy. The objective is to find a compromise among coverage efficiency, traveled distance, number of drones required, and complexity. The targets move according to one of the following three possible mobility patterns: random waypoint, Manhattan grid, and reference point group mobility patterns. The feasibility of our algorithms and their performance are also tested on a real-world indoor testbed called drone-be-gone, using Parrot *** quadcopters. The deployment confirms the results obtained with simulations and highlights the suitability of the proposed solutions for real-time applications.
In this article we review state-of-the-art concepts of space mapping and place them con- textually into the history of design optimization and modeling of microwave circuits. We formulate a generic space-mapping optim...
详细信息
In this article we review state-of-the-art concepts of space mapping and place them con- textually into the history of design optimization and modeling of microwave circuits. We formulate a generic space-mapping optimization algorithm, explain it step-by-step using a simple microstrip filter example, and then demonstrate its robustness through the fast design of an interdigital filter. Selected topics of space mapping are discussed, including implicit space mapping, gradient-based space mapping, the optimal choice of surrogate model, and tuning space mapping. We consider the application of space mapping to the modeling of microwave structures. We also discuss a software package for automated space-mapping optimization that involves both electromagnetic (EM) and circuit simulators.
In this paper, we present a new algorithm called WISER for over-the-cell channel routing in the standard cell design style using the two-layer routing model. The novelty of our approach lies in the use of ''va...
详细信息
In this paper, we present a new algorithm called WISER for over-the-cell channel routing in the standard cell design style using the two-layer routing model. The novelty of our approach lies in the use of ''vacant'' terminals for over-the-cell routing. Furthermore, we consider longest paths in the vertical constraint graph, as well as channel density as a basis for choosing nets to route over the rows of standard cells. Our approximation algorithm for net selection produces provably good results. algorithm WISER has been implemented and tested on several benchmarks, including PRIMARY1 and Deutsch's difficult example. The experimental results show that WISER reduces the channel height by an average of 29%, as compared to conventional channel routers, and 15%, as compared to existing over-the-cell routers. In addition, it reduces the total number of vias per routing by 32%.
D.A. Antoniadis' algorithm (ibid., ***-31, no.3, p.303-7, 1984) is extended to cover the computation of threshold voltage for depletion or buried-channel MOSFETs. It is shown that a key factor in its evaluation, o...
详细信息
D.A. Antoniadis' algorithm (ibid., ***-31, no.3, p.303-7, 1984) is extended to cover the computation of threshold voltage for depletion or buried-channel MOSFETs. It is shown that a key factor in its evaluation, of the derivative of the integral charge of the mobile minority carriers in the substrate with respect to the gate-source bias, can easily be calculated using the concept of flat-band capacitance. The threshold voltage is thus computed without requiring strict numerical solution of Poisson's equation, yet the accuracy is very good. This modified algorithm has been implemented in SUPREM III, and good agreement between simulation and experimental results has been achieved.< >
The discrete Fourier transform (DFT) is the standard tool for spectral analysis in digital signal processing, typically computed using the fast Fourier transform (FFT). However, for real-time applications that require...
详细信息
The discrete Fourier transform (DFT) is the standard tool for spectral analysis in digital signal processing, typically computed using the fast Fourier transform (FFT). However, for real-time applications that require recalculating the DFT at each sample or over only a subset of the N center frequencies of the DFT, the FFT is far from optimal.
暂无评论