Results 21 to 30 of about 1,355,935 (279)
Mathematics, 2021 Gravity and flexibility will cause fluctuations of the rotation angle in the servo system for flexible manipulators. The fluctuation will seriously affect the motion accuracy of end-effectors.
Dongyang Shang +3 more
semanticscholar +1 more source
Risk Prediction Algorithm of Social Security Fund Operation Based on RBF Neural Network
International Journal of Antennas and Propagation, 2021 In order to ensure the benign operation of the social security fund system, it is necessary to understand the social security fund facing all aspects of the risk, more importantly to know the relationship between different risks.
Linxuan Yang
doaj +1 more source
Configuring RBF neural networks
Electronics Letters, 1998 A novel method (based on the characteristics of scatter matrices and frequency-sensitive competitive learning) for training the hidden layer of a radial basis function neural network is proposed. The method is demonstrated to be robust and to outperform the state-of-the-art algorithm.
I. Sohn, N. Ansari
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Adaptive Robust Controller Design-Based RBF Neural Network for Aerial Robot Arm Model
Electronics, 2021 Aerial Robot Arms (ARAs) enable aerial drones to interact and influence objects in various environments. Traditional ARA controllers need the availability of a high-precision model to avoid high control chattering.
Izzat Al-Darraji +6 more
semanticscholar +1 more source
Neural networks based recognition of 3D freeform surface from 2D sketch [PDF]
, 2005 In this paper, the Back Propagation (BP) network and Radial Basis Function (RBF) neural network are employed to recognize and reconstruct 3D freeform surface from 2D freehand sketch.
Qin, SF, Sun, G, Wright, DK
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Gong-kuang zidonghua, 2014 The paper proposed a fault line selection method of small current grounding system based on wavelet de-noising and improved RBF neural network. Fault information matrix is obtained after normalization processing for maximum of absolute value of de-noised
WANG Xiaowei +3 more
doaj +1 more source
Phase transmittance RBF neural networks
Electronics Letters, 2007 Presented is a new complex valued radial basis function (RBF) neural network with phase transmittance between the input nodes and output, which makes it suitable for channel equalisation on quadrature digital modulation systems.
D.V. Loss +3 more
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Application of improved PSO-RBF neural network in the synthetic ammonia decarbonization
Journal of Hebei University of Science and Technology, 2017 The synthetic ammonia decarbonization is a typical complex industrial process, which has the characteristics of time variation, nonlinearity and uncertainty, and the on-line control model is difficult to be established. An improved PSO-RBF neural network
Yongwei LI +3 more
doaj +1 more source
Surface profile prediction and analysis applied to turning process [PDF]
, 2008 An approach for the prediction of surface profile in turning process using Radial Basis Function (RBF) neural networks is presented. The input parameters of the RBF networks are cutting speed, depth of cut and feed rate.
COSTES, Jean-Philippe, LU, Chen
core +6 more sources
Complexity, 2018 The neural network has the advantages of self-learning, self-adaptation, and fault tolerance. It can establish a qualitative and quantitative evaluation model which is closer to human thought patterns.
Tiantian Luan +3 more
doaj +1 more source