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检索条件"主题词=Gradient descent algorithm"

共 255 条记录，以下是181-190 订阅

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gradient-based Optimization for Unrepeatered Optical Systems

Gradient-based Optimization for Unrepeatered Optical Systems

引用

18th SBMO International Conference / 12th SBMO/IEEE MTT-S International Microwave and Optoelectronics Conference (IMOC)

作者： Junior, Jose Helio C. Della Lucia, Felipe L. Sutili, Tiago Mello, Darli A. A. Figueiredo, Rafael C. CPqD Fdn Opt Technol Div Campinas Brazil Univ Estadual Campinas Sch Elect & Comp Engn Campinas Brazil

ISBN: (纸本)9781728130996

We propose a multi-parameter adaptive technique based on the gradient descent algorithm (MAT-GRAD) for optimizing the amplification scheme in unrepeatered wavelength-division multiplexed optical systems. The proposed methodology uses the gradient descent method to jointly optimize the transmitter (Tx) and receiver (Rx) remote optically pumped amplifiers (ROPAs), as well as the Tx forward first- order distributed Raman amplifier ( DRA). The MAT-GRAD algorithm is evaluated in combination with the conventional gradient descent algorithm (GDA), and GDA with momentum (GDAM). The simulations indicate that the MAT-GRAD with GDAM achieves a suitable minimum at a higher convergence speed.

关键词： Unrepeatered systems gradient descent algorithm gradient descent algorithm with momentum

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IMPROVED ONLINE IDENTIFICATION OF ACOUSTIC MISO SYSTEMS BASED ON SEPARATED INPUT SIGNAL COMPONENTS

IMPROVED ONLINE IDENTIFICATION OF ACOUSTIC MISO SYSTEMS BASE...

引用

IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Thuene, Philipp Enzner, Gerald Ruhr Univ Bochum Inst Commun Acoust IKA Bochum Germany

ISBN: (纸本)9781479903566

Creating an immersive listening experience and providing the audience with improved spatial realism is the goal of many adaptive audio reproduction techniques such as room equalization or crosstalk cancellation. The majority of these approaches currently relies on acoustic impulse responses (AIRs) that have been measured prior to the actual audio reproduction. In order to maintain a high degree of adaptivity, however, the AIRs need to be estimated online during the reproduction process, which turns out to be a severely ill-conditioned problem due to the high inter-channel correlation of the loudspeaker signals. In this paper, we present a novel approach to MISO system identification with realistically correlated excitation. Based on the idea of separate treatment of correlated and uncorrelated signal components, we propose two extended filter structures for gradient-descent-based adaptive system identification and provide theoretical analysis and experimental validation of their effectiveness.

关键词： room acoustics multichannel acoustic system identification nonuniqueness gradient descent algorithm

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Medical Diagnosis Applications Using a Novel Interactively Recurrent Self-evolving Fuzzy CMAC Model

Medical Diagnosis Applications Using a Novel Interactively R...

引用

International Joint Conference on Neural Networks (IJCNN)

作者： Wang, Jyun-Guo Tai, Shen-Chuan Lin, Cheng-Jian Natl Cheng Kung Univ Inst Comput & Commun Engn Tainan 701 Taiwan Natl Chin Yi Univ Technol Dept Comput Sci & Inf Engn Taichung Taiwan

ISBN: (纸本)9781479914845

In this paper, a recurrent self-evolving Fuzzy Cerebellar Model Articulation Controller (FCMAC) model for classification problems is developed, namely the interactively recurrent self-evolving fuzzy Cerebellar Model Articulation Controller (IRSFCMAC). The interactively recurrent structure in an IRSFCMAC is formed as external loops and internal feedbacks by feeding the rule firing strength to itself and others rules. The IRSFCMAC learning starts with an empty rule base and all of rules are generated and learned online, through a simultaneous structure and parameter learning, while the relative parameters are learned through a gradient descent algorithm. The proposed IRSFCMAC is tested by the four benchmarked classification problems and compared with the well-known traditional FCMAC. Experimental results show that the proposed IRSFCMAC model enhanced classification performance results, in terms of accuracy and RMSE.

关键词： interactively recurrent self-evolving fuzzy Cerebellar Model Articulation Controller gradient descent algorithm

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Rapid Configuration of Optical Processor Based on Reconfigurable Multiport Interferometer

Rapid Configuration of Optical Processor Based on Reconfigur...

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Asia Communications and Photonics Conference (ACP) / International Conference on Information Photonics and Optical Communications (IPOC)

作者： Zhao, Wanyu Dan, Yihang Fan, Zeyang Zhang, Tian Xu, Kun Beijing Univ Posts & Telecommun State Key Lab Informat Photon & Opt Commun Beijing 100876 Peoples R China

ISBN: (纸本)9781665481557

We demonstrate an optimization method for universal multiport interferometers to perform rapid configuration reconstruction. This method uses deep learning to model the relationship between the transmission characteristics and the configuration parameters of the component of the reconfigurable multiport interferometers, making it resistant to manufacturing flaws of the interferometer. Our demonstration provides a potential way to implement fast and accurate reconfiguration functions for optical processors.

关键词： reconfigurable multiple interferometers network optical signal processing gradient descent algorithm

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Model Predictive Assisting Control of Vehicle Following Task Based on Driver Model

Model Predictive Assisting Control of Vehicle Following Task...

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IEEE International Conference on Control Applications Part of 2010 IEEE Multi-Conference on Systems and Control

作者： Mikami, Koji Okuda, Hiroyuki Taguchi, Shun Tazaki, Yuichi Suzuki, Tatsuya Nagoya Univ Mech Sci & Engn Chikusa Ku Furo Cho Nagoya Aichi 4648601 Japan Toyota Cent Res & Dev Labs Inc Nagakute Aichi Japan JST CREST Program Tokyo Japan

ISBN: (纸本)9781424453634

A personalized driver assisting system that makes use of the driver's behavior model is developed. As a model of driving behavior, the Probability-weighted ARX (PrARX) model, a type of hybrid dynamical system models, is introduced. A PrARX model that describes the driver's vehicle-following skill on expressways is identified using a simple gradient descent algorithm from actual driving data collected on a driving simulator. The obtained PrARX model describes the driver's logical decision making as well as continuous maneuver in a uniform manner. Finally, the optimization of the braking assist is formulated as a mixed-integer linear programming (MILP) problem using the identified driver model, and computed online in the model predictive control framework.

关键词： MILP problem PrARX model driver behavior model driver information systems driver model driving simulator expressways gradient descent algorithm gradient methods logical decision making mixed-integer linear programming model predictive assisting control personalized driver assisting system predictive control probability-weighted ARX road vehicles vehicle following task vehicle-following skill

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Fuzzy Model Control for Maglev Suspension System

Fuzzy Model Control for Maglev Suspension System

引用

International Conference on System Science and Engineering (ICSSE)

作者： Su, Kuo-Ho Duy-Thanh Pham Tsung, Tsing-Tshih Yang, Chan-Yun Chinese Culture Univ Grad Inst Digital Mechatron Technol 55 Hwa Kang Rd Taipei 11114 Taiwan Natl Taipei Univ Dept Elect Engn New Taipei Taiwan

ISBN: (纸本)9781614995227;9781614995210

The maglev suspension system or magnetic levitation system (MLS), using the electromagnetic force to float, can effectively reduce the mechanical vibration friction and wearing loss caused by contact operation. However the parameters in the mathematical model are related to the permanent magnet geometry, distance and the total mass of the platform. To achieve fast response, a fuzzy system and the parameter identification algorithm for maglev suspension system are proposed in the paper. The proposed first fuzzy model method is based on the table lookup scheme (TLS) to establish a common fuzzy system procedure. By gathering the input and output data pairs, a fuzzy system is created to replace the currently used mathematical model. On the other hand, due to the parameters are related to the hardware structure, the second gradient descent algorithm (GDA) is proposed. By using the gathered data pairs, the parameters of membership functions are updated through the gradient descent algorithm. In this paper, the fuzzy model systems based on TLS and GDA are applied to ensure the effectiveness of tracking performance by replacing the mathematical model of MLS. From the results, the chattering phenomenon is reduced and fast response can be obtained without degrading the tracking performance.

关键词： maglev suspension system fuzzy control fuzzy model system gradient descent algorithm

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Coupling Timing Objectives with Optical Proximity Correction for Improved Timing Yield

Coupling Timing Objectives with Optical Proximity Correction...

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12th International Symposium on Quality Electronic Design (ISQED)

作者： Banerjee, Shayak Agarwal, Kanak B. Nassif, Sani R. Culp, James A. Liebmann, Lars W. Orshansky, Michael Univ Texas Austin Austin TX 78712 USA IBM Austin Res Lab Austin TX 78758 USA IBM Microelect East Fishkill NY 12533 USA

ISBN: (纸本)9781612849140

Design-manufacturing co-optimization has been earmarked as a key enabler of future technology scaling. Current manufacturing methods treat all transistors equally irrespective of their criticality in the design flow. In the presence of variations in the lithographic process, this leads to timing violations which reduces chip yield. In this paper, we develop a timing-driven process window optical proximity correction (TD-PWOPC) algorithm that tunes the mask generation for each transistor based on its electrical criticality in the design. Our method utilizes knowledge of timing information to generate delay bounds on each cell. It then develops a process variation aware OPC cost function for each cell to ensure that post-lithography delay lies within these bounds. This method uses a single image simulation coupled with simplified models for regular polysilicon layouts to predict though-process performance. We finally use a gradient-descent algorithm to minimize this cost function. Results show that the use of TD-PWOPC can reduce delay errors significantly compared to regular OPC at small runtime overheads of 4.5%.

关键词： Cost function Delay Lithography Logic gates Sensitivity TD-PWOPC Transistors chip yield cost function coupling timing objectives delay bounds design flow design for manufacture design-manufacturing co-optimization electrical criticality gradient descent algorithm gradient methods integrated circuit yield lithographic process mask generation post-lithography delay proximity effect (lithography) runtime overhead timing yield timing-driven process window optical proximity correction

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A NOVEL SPATIALLY CONSTRAINED MIXTURE MODEL FOR IMAGE SEGMENTATION 19

A NOVEL SPATIALLY CONSTRAINED MIXTURE MODEL FOR IMAGE SEGMEN...

引用

19th International Conference on Digital Signal Processing (DSP)

作者： Xiao, Zhiyong Yuan, Yunhao Yang, Jinlong Ge, Hongwei Jiangnan Univ Sch Internet Things Engn Wuxi 214122 Peoples R China

ISBN: (纸本)9781479946129

We present a novel spatially constrained mixture model for image segmentation. This model assumes that the prior distribution for each pixel depends on its neighboring pixels', and the degree of dependency is decided by the geometric closeness. The negative log-likelihood function of the proposed method is viewed as energy function, and the parameters of the energy function are estimated by gradient descent algorithm. Evaluation of the developed method is done on synthetic and real world images. Experimental results are compared with those obtained using mixture model-based methods. The proposed approach performs better than other ones in terms of classification accuracy.

关键词： Mixture model spatial constraint energy function gradient descent algorithm image segmentation

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Intelligent controller using neural network

Intelligent controller using neural network

引用

International Conference on Intelligent Manufacturing (ICIM 95)

作者： WANG, J WANG, FL ZHANG, JL ZHANG, J NE UNIV TECHNOL DEPT AUTOMAT CONTROLSHENYANG 110006PEOPLES R CHINA

ISBN: (纸本)0819420123

This paper presents an intelligent PID controller based on a gradient descent learning algorithm. A BP neural network is needed to learn the characteristics of the dynamic systems. The possibility of using neural network models directly within a model-based predictive control strategy is also considered by making use of an on-line optimization routine to determine the future inputs that will minimize the deviation between the desired and predicted outputs. The controller's structure and the learning algorithm are very simple and easily realized. It can also replace the traditional PID controller, control the complex systems, and require neither process model nor more tuning parameters.

关键词： BP NEURAL NETWORKS PID CONTROLLER PREDICTIVE CONTROL NONLINEAR SYSTEMS gradient descent algorithm

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Convergence Analysis of Interval Feedforward Neural Networks 34

Convergence Analysis of Interval Feedforward Neural Networks

引用

34th Chinese Control and Decision Conference (CCDC)

作者： Guan, Shouping Liang, Yue Yu, Xiaoyu Northeastern Univ Coll Informat Sci & Engn Shenyang 110819 Peoples R China

ISBN: (纸本)9781665478960

In practical application of neural networks, we often try to change some factors to make the algorithm perform better, but the convergence analysis of the algorithm cannot keep up with it in time. This paper studies the convergence of interval feedforward neural network (IFNN). First the convergence of the IFNN is derived theoretically based on gradient descent algorithm, where the IFNN possesses the interval input and output but the point weights;Then, by means of numerical analysis, the relationship between the convergence of general IFNN and interval weights is discussed. In the numerical analysis, the coverage of interval output is taken as the objective function, and the particle swarm optimization (PSO) algorithm is used for optimizing to ensure the interval network output approaching the interval width range of the weight and threshold of the point output. Studying the convergence of interval neural networks (INNs) can effectively promote the application range of INNs, making INNs better used in uncertain systems, reducing the impact of fluctuations, noise and measurement errors, and improving the objectivity and robustness of industrial process modeling.

关键词： Interval Neural Network gradient descent algorithm Convergence Information Granularity

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