The Experts below are selected from a list of 787053 Experts worldwide ranked by ideXlab platform
Natalia K. Nikolova - One of the best experts on this subject based on the ideXlab platform.
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Adjoint-accelerated Design Framework for novel materials in microwave applications
2011Co-Authors: Ali Khalatpour, Qingsha S Cheng, John W. Bandler, Reza K. Amineh, Natalia K. NikolovaAbstract:A Design Framework is introduced to expedite the Design of novel material structures. We apply an adjoint-accelerated space mapping that takes advantage of adjoint sensitivities of the fine model. We show a sensitivity-enabled Design Framework that easily implements both space mapping and direct optimization. A flat lens and a π-shaped resonator are Designed.
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A space-mapping Design Framework
IEEE Transactions on Microwave Theory and Techniques, 2004Co-Authors: John W. Bandler, Daniel M. Hailu, Qingsha S Cheng, Natalia K. NikolovaAbstract:We present a comprehensive microwave Design Framework for implementing the original, aggressive, implicit, and response residual space-mapping (SM) approaches through widely available software. General steps and tools for possible SM implementations are elaborated. Our presentation is a reference guide for microwave Designers using the SM technique. An instructive "multiple cheese-cutting" example demonstrates the SM approach to engineering Design and some possible pitfalls. For the first time, an ADS Framework implements the SM steps interactively. A three-section transformer example illustrates the approach, step by step. A six-section H-plane waveguide filter Design emerges after four iterations, using the implicit SM and the response-residual space-mapping (RRSM) optimization entirely within the Design Framework. An RRSM surrogate is developed to match the fine (HFSS) model. We use sparse frequency sweeps and do not require Jacobians of the fine model.
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An implementable space mapping Design Framework
2004 IEEE MTT-S International Microwave Symposium Digest (IEEE Cat. No.04CH37535), 1Co-Authors: John W. Bandler, Daniel M. Hailu, Qingsha S Cheng, Natalia K. NikolovaAbstract:We present a microwave Design Framework for implementing an implicit and response residual space mapping (RRSM) approach. The RRSM surrogate is matched to the fine model. An intuitive "multiple cheese-cutting" example demonstrates the concept. For the first time, an ADS Framework implements the space mapping (SM) steps interactively. A six-section H-plane waveguide filter Design emerges after four iterations, using the implicit SM and RRSM optimization entirely within the Design Framework. We use sparse frequency sweeps and do not use the Jacobian of the fine model.
John W. Bandler - One of the best experts on this subject based on the ideXlab platform.
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Adjoint-accelerated Design Framework for novel materials in microwave applications
2011Co-Authors: Ali Khalatpour, Qingsha S Cheng, John W. Bandler, Reza K. Amineh, Natalia K. NikolovaAbstract:A Design Framework is introduced to expedite the Design of novel material structures. We apply an adjoint-accelerated space mapping that takes advantage of adjoint sensitivities of the fine model. We show a sensitivity-enabled Design Framework that easily implements both space mapping and direct optimization. A flat lens and a π-shaped resonator are Designed.
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A space-mapping Design Framework
IEEE Transactions on Microwave Theory and Techniques, 2004Co-Authors: John W. Bandler, Daniel M. Hailu, Qingsha S Cheng, Natalia K. NikolovaAbstract:We present a comprehensive microwave Design Framework for implementing the original, aggressive, implicit, and response residual space-mapping (SM) approaches through widely available software. General steps and tools for possible SM implementations are elaborated. Our presentation is a reference guide for microwave Designers using the SM technique. An instructive "multiple cheese-cutting" example demonstrates the SM approach to engineering Design and some possible pitfalls. For the first time, an ADS Framework implements the SM steps interactively. A three-section transformer example illustrates the approach, step by step. A six-section H-plane waveguide filter Design emerges after four iterations, using the implicit SM and the response-residual space-mapping (RRSM) optimization entirely within the Design Framework. An RRSM surrogate is developed to match the fine (HFSS) model. We use sparse frequency sweeps and do not require Jacobians of the fine model.
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An implementable space mapping Design Framework
2004 IEEE MTT-S International Microwave Symposium Digest (IEEE Cat. No.04CH37535), 1Co-Authors: John W. Bandler, Daniel M. Hailu, Qingsha S Cheng, Natalia K. NikolovaAbstract:We present a microwave Design Framework for implementing an implicit and response residual space mapping (RRSM) approach. The RRSM surrogate is matched to the fine model. An intuitive "multiple cheese-cutting" example demonstrates the concept. For the first time, an ADS Framework implements the space mapping (SM) steps interactively. A six-section H-plane waveguide filter Design emerges after four iterations, using the implicit SM and RRSM optimization entirely within the Design Framework. We use sparse frequency sweeps and do not use the Jacobian of the fine model.
Hugo De Man - One of the best experts on this subject based on the ideXlab platform.
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FPL - Development of a Design Framework for Platform-Independent Networked Reconfiguration of Software and Hardware
Field-Programmable Logic and Applications, 2001Co-Authors: Bingfeng Mei, Patrick Schaumont, Serge Vernalde, Rudy Lauwereins, Hugo De ManAbstract:The rapid development of the Internet opens wide opportunities for various types of network services. Development of new network services need the support of a powerful Design Framework. This paper describes such a Design Framework that can help service providers to build platform independent hardware-software co-Designed services. Those new services consist of both software and hardware components, which can be reconfigured through the network. The new Design Framework can be considered as a Java Framework with a hardware extension. Part of the measurement results and an application demonstrator are given.
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development of a Design Framework for platform independent networked reconfiguration of software and hardware
Lecture Notes in Computer Science, 2001Co-Authors: Bingfeng Mei, Patrick Schaumont, Serge Vernalde, Rudy Lauwereins, Hugo De ManAbstract:The rapid development of the Internet opens wide opportunities for various types of network services. Development of new network services need the support of a powerful Design Framework. This paper describes such a Design Framework that can help service providers to build platform independent hardware-software co-Designed services. Those new services consist of both software and hardware components, which can be reconfigured through the network. The new Design Framework can be considered as a Java Framework with a hardware extension. Part of the measurement results and an application demonstrator are given.
Qingsha S Cheng - One of the best experts on this subject based on the ideXlab platform.
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Automated EM-level Design Framework for sequential coupled resonator filters
2017Co-Authors: Xiaolin Fan, Qingsha S Cheng, Paul D. Laforge, Slawomir KozielAbstract:An efficient fully automated EM-level Design Framework is implemented using Matlab, Sonnetlab toolbox and Sonnet EM simulator for the Design of different type of sequentially coupled resonator planar filters. The proposed implementation integrates the space mapping technique and reflected group delay method to achieve fast and reliable EM-based filter Design. In this paper, two Design examples are given to validate the performance of the proposed Design Framework.
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Adjoint-accelerated Design Framework for novel materials in microwave applications
2011Co-Authors: Ali Khalatpour, Qingsha S Cheng, John W. Bandler, Reza K. Amineh, Natalia K. NikolovaAbstract:A Design Framework is introduced to expedite the Design of novel material structures. We apply an adjoint-accelerated space mapping that takes advantage of adjoint sensitivities of the fine model. We show a sensitivity-enabled Design Framework that easily implements both space mapping and direct optimization. A flat lens and a π-shaped resonator are Designed.
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A space-mapping Design Framework
IEEE Transactions on Microwave Theory and Techniques, 2004Co-Authors: John W. Bandler, Daniel M. Hailu, Qingsha S Cheng, Natalia K. NikolovaAbstract:We present a comprehensive microwave Design Framework for implementing the original, aggressive, implicit, and response residual space-mapping (SM) approaches through widely available software. General steps and tools for possible SM implementations are elaborated. Our presentation is a reference guide for microwave Designers using the SM technique. An instructive "multiple cheese-cutting" example demonstrates the SM approach to engineering Design and some possible pitfalls. For the first time, an ADS Framework implements the SM steps interactively. A three-section transformer example illustrates the approach, step by step. A six-section H-plane waveguide filter Design emerges after four iterations, using the implicit SM and the response-residual space-mapping (RRSM) optimization entirely within the Design Framework. An RRSM surrogate is developed to match the fine (HFSS) model. We use sparse frequency sweeps and do not require Jacobians of the fine model.
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An implementable space mapping Design Framework
2004 IEEE MTT-S International Microwave Symposium Digest (IEEE Cat. No.04CH37535), 1Co-Authors: John W. Bandler, Daniel M. Hailu, Qingsha S Cheng, Natalia K. NikolovaAbstract:We present a microwave Design Framework for implementing an implicit and response residual space mapping (RRSM) approach. The RRSM surrogate is matched to the fine model. An intuitive "multiple cheese-cutting" example demonstrates the concept. For the first time, an ADS Framework implements the space mapping (SM) steps interactively. A six-section H-plane waveguide filter Design emerges after four iterations, using the implicit SM and RRSM optimization entirely within the Design Framework. We use sparse frequency sweeps and do not use the Jacobian of the fine model.
Daniel M. Hailu - One of the best experts on this subject based on the ideXlab platform.
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A space-mapping Design Framework
IEEE Transactions on Microwave Theory and Techniques, 2004Co-Authors: John W. Bandler, Daniel M. Hailu, Qingsha S Cheng, Natalia K. NikolovaAbstract:We present a comprehensive microwave Design Framework for implementing the original, aggressive, implicit, and response residual space-mapping (SM) approaches through widely available software. General steps and tools for possible SM implementations are elaborated. Our presentation is a reference guide for microwave Designers using the SM technique. An instructive "multiple cheese-cutting" example demonstrates the SM approach to engineering Design and some possible pitfalls. For the first time, an ADS Framework implements the SM steps interactively. A three-section transformer example illustrates the approach, step by step. A six-section H-plane waveguide filter Design emerges after four iterations, using the implicit SM and the response-residual space-mapping (RRSM) optimization entirely within the Design Framework. An RRSM surrogate is developed to match the fine (HFSS) model. We use sparse frequency sweeps and do not require Jacobians of the fine model.
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An implementable space mapping Design Framework
2004 IEEE MTT-S International Microwave Symposium Digest (IEEE Cat. No.04CH37535), 1Co-Authors: John W. Bandler, Daniel M. Hailu, Qingsha S Cheng, Natalia K. NikolovaAbstract:We present a microwave Design Framework for implementing an implicit and response residual space mapping (RRSM) approach. The RRSM surrogate is matched to the fine model. An intuitive "multiple cheese-cutting" example demonstrates the concept. For the first time, an ADS Framework implements the space mapping (SM) steps interactively. A six-section H-plane waveguide filter Design emerges after four iterations, using the implicit SM and RRSM optimization entirely within the Design Framework. We use sparse frequency sweeps and do not use the Jacobian of the fine model.
