- 标题
- 摘要
- 关键词
- 实验方案
- 产品
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Based on Spectrum Modeling and Optimization
摘要： Bistatic synthetic aperture radar (SAR) is able to break through the limitation of monostatic SAR on forward-looking area imaging with appropriate geometry configurations. Thanks to such an ability, bistatic forward-looking SAR (BFSAR) has extensive potential practical applications. For the focusing problem of conventional side-looking SAR, ω–k algorithm is accepted as the ideal solution. In this paper, the ω–k algorithm will be discussed in BFSAR geometry. As for the bistatic configuration, spatial domain linearization procedure should be carried out to extract a range variable from the point target reference spectrum (PTRS) in the existing ω–k algorithms. With respect to the BFSAR geometry, nevertheless, the linearization procedure reduces the accuracy of PTRS seriously. To cope with such a problem, a novel ω–k algorithm for BFSAR is proposed. In the proposed method, the range variable is modeled as a parameterized polynomial, and the corresponding PTRS with respect to two-dimensional frequencies is established. Then, the parameters are estimated by differential evolution to minimize the PTRS errors for each range coordinate and frequency point. Based on the estimated PTRS, the BFSAR data can be focused well by the proposed ω–k algorithm. Simulation results verify the effectiveness of the proposed method.
关键词： Bistatic forward-looking synthetic aperture radar (BFSAR),differential evolution (DE),ω–k,point target reference spectrum (PTRS)
更新于2025-09-23 15:23:52
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[IEEE 2018 IEEE 3rd International Conference on Image, Vision and Computing (ICIVC) - Chongqing (2018.6.27-2018.6.29)] 2018 IEEE 3rd International Conference on Image, Vision and Computing (ICIVC) - Improved Differential Evolution with Parameter Adaption Based on Population Diversity
摘要： The differential evolution algorithm is an important branch of the bionic intelligent computation, which uses the Darwinian population's evolutionary principle: survival of the fittest and survival of the fittest. Due to the simple implement and few parameters, many researchers have invested into the study of the algorithm and proposed a large number of differential evolution variants. For the existing differential evolution algorithm, once the size of the population is determined, the size of the search range is fixed. Based on the global diversity of population, we focus on controlling the value of the search parameters p. In the proposal, after normalizing the population diversity, each individual will select its unique search scope according to the diversity conditions. Therefore, the proposed method can balance between the global search and the local search. According to our extensive experimental results on various benchmark functions, the proposed method outperform other compared advanced algorithms.
关键词： population diversity,SHADE,differential evolution
更新于2025-09-23 15:22:29
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Vector quantization using the improved differential evolution algorithm for image compression
摘要： Vector quantization (VQ) is a popular image compression technique with a simple decoding architecture and high compression ratio. Codebook designing is the most essential part in vector quantization. Linde–Buzo–Gray (LBG) is a traditional method of generation of VQ codebook which results in lower PSNR value. A codebook affects the quality of image compression, so the choice of an appropriate codebook is a must. Several optimization techniques have been proposed for global codebook generation to enhance the quality of image compression. In this paper, a novel algorithm called IDE-LBG is proposed which uses improved differential evolution algorithm coupled with LBG for generating optimum VQ codebooks. The proposed IDE works better than the traditional DE with modifications in the scaling factor and the boundary control mechanism. The IDE generates better solutions by efficient exploration and exploitation of the search space. Then the best optimal solution obtained by the IDE is provided as the initial codebook for the LBG. This approach produces an efficient codebook with less computational time and the consequences include excellent PSNR values and superior quality reconstructed images. It is observed that the proposed IDE-LBG find better VQ Codebooks as compared to IPSO-LBG, BA-LBG and FA-LBG.
关键词： Improved differential evolution (IDE) algorithm,Improved particle swarm optimization (IPSO) algorithm,Bat algorithm (BA),Firefly algorithm (FA),Vector quantization,Image compression,Codebook,Linde–Buzo–Gray (LBG) algorithm
更新于2025-09-23 15:22:29
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OPTIMAL DESIGN OF A KU/KA-BAND WIDE-FLARE-ANGLE CORRUGATED HORN USING THE DIFFERENTIAL EVOLUTION ALGORITHM
摘要： A novel wide-flare-angle corrugated horn covering the full Ku/Ka satellite communication frequency bands is designed and optimized. In order to satisfy the rigorous bandwidth requirements, a spline-profiled smooth section and a corrugated section with ring-loaded slots are introduced into the wide-flare-angle horn design. Instead of the “trial-and-error” method, the Differential Evolution (DE) algorithm is employed to obtain the optimum dimensions of the proposed horn. A prototype of the optimized horn is constructed and measured. Both simulated and measured results show that the proposed horn has good radiation and impedance performance. The performance of the horn is also demonstrated as a feed in a typical dual-reflector antenna. Simulation results show that the overall antenna system meets the usual performance requirements.
关键词： Ku/Ka-band,satellite communication,wide-flare-angle corrugated horn,Differential Evolution algorithm
更新于2025-09-23 15:21:21
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Outage and BER performances of indoor relay-assisted hybrid RF/VLC systems
摘要： In this study, the authors analyse the outage performance of the indoor relay-assisted hybrid radio frequency (RF)/visible light communication (VLC) systems. They derive closed-form expressions for the outage probability of the end-to-end signal-to-noise ratio. Then they obtain the optimal approximation parameter with optimising the outage probability using the differential evolution algorithm. Moreover, they analysed the average bit error rate (BER) performance of the hybrid RF/optical system using pulse position modulation method while assuming the timing error in synchronisation. Finally, they present some numerical results utilising the newly derived exact closed-form expressions.
关键词： pulse position modulation,hybrid RF/VLC,BER,differential evolution algorithm,relay-assisted,outage probability
更新于2025-09-23 15:21:21
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[IEEE 2019 IEEE 46th Photovoltaic Specialists Conference (PVSC) - Chicago, IL, USA (2019.6.16-2019.6.21)] 2019 IEEE 46th Photovoltaic Specialists Conference (PVSC) - Understanding Measurement Artifacts Causing Inherent Cation Gradients in Depth Profiles of Perovskite Photovoltaics with TOF-SIMS
摘要： Utilizing cumulative correlation information already existing in an evolutionary process, this paper proposes a predictive approach to the reproduction mechanism of new individuals for differential evolution (DE) algorithms. DE uses a distributed model (DM) to generate new individuals, which is relatively explorative, whilst evolution strategy (ES) uses a centralized model (CM) to generate offspring, which through adaptation retains a convergence momentum. This paper adopts a key feature in the CM of a covariance matrix adaptation ES, the cumulatively learned evolution path (EP), to formulate a new evolutionary algorithm (EA) framework, termed DEEP, standing for DE with an EP. Without mechanistically combining two CM and DM based algorithms together, the DEEP framework offers advantages of both a DM and a CM and hence substantially enhances performance. Under this architecture, a self-adaptation mechanism can be built inherently in a DEEP algorithm, easing the task of predetermining algorithm control parameters. Two DEEP variants are developed and illustrated in the paper. Experiments on the CEC’13 test suites and two practical problems demonstrate that the DEEP algorithms offer promising results, compared with the original DEs and other relevant state-of-the-art EAs.
关键词： evolution path (EP),Cumulative learning,evolutionary computation,differential evolution (DE)
更新于2025-09-23 15:19:57
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[IEEE 2019 IEEE 21st Electronics Packaging Technology Conference (EPTC) - Singapore, Singapore (2019.12.4-2019.12.6)] 2019 IEEE 21st Electronics Packaging Technology Conference (EPTC) - Smart White LEDs with Tunable Correlated Color Temperatures through Single-Chip Packaging
摘要： This paper studies the optimization problem of topological active net (TAN), which is often seen in image segmentation and shape modeling. A TAN is a topological structure containing many nodes, whose positions must be optimized while a prede?ned topology needs to be maintained. TAN optimization is often time-consuming and even constructing a single solution is hard to do. Such a problem is usually approached by a “best improvement local search” (BILS) algorithm based on deterministic search (DS), which is inef?cient because it spends too much efforts in nonpromising probing. In this paper, we propose the use of micro-differential evolution (DE) to replace DS in BILS for improved directional guidance. The resultant algorithm is termed deBILS. Its micro-population ef?ciently utilizes historical information for potentially promising search directions and hence improves ef?ciency in probing. Results show that deBILS can probe promising neighborhoods for each node of a TAN. Experimental tests verify that deBILS offers substantially higher search speed and solution quality not only than ordinary BILS, but also the genetic algorithm and scatter search algorithm.
关键词： grid deformation,topological active net (TAN),structure optimization,Differential evolution (DE),topological optimization
更新于2025-09-23 15:19:57
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[IEEE 2019 Conference on Lasers and Electro-Optics Europe & European Quantum Electronics Conference (CLEO/Europe-EQEC) - Munich, Germany (2019.6.23-2019.6.27)] 2019 Conference on Lasers and Electro-Optics Europe & European Quantum Electronics Conference (CLEO/Europe-EQEC) - Type II Excitability with Quantum Dot Lasers: Canards, Bistabilities and More
摘要： This paper studies the optimization problem of topological active net (TAN), which is often seen in image segmentation and shape modeling. A TAN is a topological structure containing many nodes, whose positions must be optimized while a prede?ned topology needs to be maintained. TAN optimization is often time-consuming and even constructing a single solution is hard to do. Such a problem is usually approached by a “best improvement local search” (BILS) algorithm based on deterministic search (DS), which is inef?cient because it spends too much efforts in nonpromising probing. In this paper, we propose the use of micro-differential evolution (DE) to replace DS in BILS for improved directional guidance. The resultant algorithm is termed deBILS. Its micro-population ef?ciently utilizes historical information for potentially promising search directions and hence improves ef?ciency in probing. Results show that deBILS can probe promising neighborhoods for each node of a TAN. Experimental tests verify that deBILS offers substantially higher search speed and solution quality not only than ordinary BILS, but also the genetic algorithm and scatter search algorithm.
关键词： grid deformation,topological active net (TAN),structure optimization,Differential evolution (DE),topological optimization
更新于2025-09-23 15:19:57
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Design and development of symmetrical super-lift DCa??AC converter using firefly algorithm for solar-photovoltaic applications
摘要： Since dynamic economic dispatch with wind power uncertainty poses great challenges for power system operation due to its non-linear and uncertain characteristics, this paper proposes a robust optimization model with different levels of uncertainty budget. The dynamic economic dispatch problem is converted into the robust optimization model with an uncertainty budget, which transforms the non-deterministic model into a deterministic optimization problem. Differential evolution is improved by the sequential quadratic programming method and utilized to solve the robust optimization model. Due to the complex-coupled constraints among thermal units, several constraint-handling procedures are proposed to address those constraint limits, which have a significant impact on the efficiency of the whole optimization. The robust optimization model with an adjustable uncertainty budget is implemented in two test systems. The results obtained for the first test system prove the efficiency of differential evolution-based sequential quadratic programming and the constraint-handling procedures; the performance of the second test system reveals that the robust optimization method with different levels of uncertainty budget provides a promising method for solving the dynamic economic dispatch problem with wind power uncertainty.
关键词： robust optimization,Dynamic economic dispatch,uncertainty budget,differential evolution,sequential quadratic programming,wind power
更新于2025-09-23 15:19:57
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[IEEE 2019 International Conference on Computer, Communication, Chemical, Materials and Electronic Engineering (IC4ME2) - Rajshahi, Bangladesh (2019.7.11-2019.7.12)] 2019 International Conference on Computer, Communication, Chemical, Materials and Electronic Engineering (IC4ME2) - Low Loss Microstructure Optical Fiber Refractive Index Sensor based on Surface Plasmon Resonance
摘要： This paper studies the optimization problem of topological active net (TAN), which is often seen in image segmentation and shape modeling. A TAN is a topological structure containing many nodes, whose positions must be optimized while a prede?ned topology needs to be maintained. TAN optimization is often time-consuming and even constructing a single solution is hard to do. Such a problem is usually approached by a “best improvement local search” (BILS) algorithm based on deterministic search (DS), which is inef?cient because it spends too much efforts in nonpromising probing. In this paper, we propose the use of micro-differential evolution (DE) to replace DS in BILS for improved directional guidance. The resultant algorithm is termed deBILS. Its micro-population ef?ciently utilizes historical information for potentially promising search directions and hence improves ef?ciency in probing. Results show that deBILS can probe promising neighborhoods for each node of a TAN. Experimental tests verify that deBILS offers substantially higher search speed and solution quality not only than ordinary BILS, but also the genetic algorithm and scatter search algorithm.
关键词： grid deformation,topological active net (TAN),structure optimization,Differential evolution (DE),topological optimization
更新于2025-09-23 15:19:57