wavelet neural network
COMPARING EVOLUTIONARY ALGORITHMS ON TUNING THE PARAMETERS OF FUZZY WAVELET NEURAL NETWORK
... Fuzzy Wavelet Neural Network (FWNN) has been used as one of the most effective methods of soft ...a Neural Network that has been combined by fuzzy rules for dealing with complex ...
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Verification of an Evolutionary-based Wavelet Neural Network Model for Nonlinear Function Approximation
... Nonlinear function approximation is one of the most important tasks in system analysis and identification. Several models have been presented to achieve an accurate approximation on nonlinear mathematics functions. ...
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Application of Local Linear Wavelet Neural Network in Short Term Electric Load Forecasting
... above wavelet neural network is a kind of basis function neural network in the sense of that the wavelet consists of the basis ...perceptron neural network, this ...
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Adaptive Wavelet Neural Network for Terrestrial Laser Scanner-Based Crack Detection
... adaptive wavelet neural network (WNN)-based approach to compress data into a combination of low- and high-resolution surfaces, and automatically detect concrete cracks and other forms of ...layer ...
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The Prediction of Stock Price Based on Improved Wavelet Neural Network
... the wavelet analysis theory developed in the mid-1980, WNN was first proposed by Qinghua Zhang, and has been widely applied [6], WNN has following advantages, one is that as the low correla- tion of wavelet ...
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Wavelet Neural Network: A Hybrid Method in Modeling Heterogeneous Reservoirs
... the wavelet neural network (WNN) requires less CPU time than the ordinary kriging (OK) and multilayer perceptron neural network (MLP) ...
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HHT Fuzzy Wavelet Neural Network to Identify Incipient Cavitations in Cooling pump of Engine
... The neural network and fuzzy theory are two effective identification ...fuzzy wavelet neural network (FWNN) integrates the advantages of both fuzzy technique and wavelet ...
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Wavelet Neural Network for Classification of Bundle Branch Blocks
... a neural network using wavelet function as activation function in hidden layer ...designed wavelet neural network (WNN) was adopted to classify bundle branch ...with ...
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Human lower extremity joint moment prediction: A wavelet neural network approach
... the wavelet neural network to calculate lower extremity joint moments using ground reaction forces and electromyography signals; easier and faster than multi body dynamics and more accurate than feed ...
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Estimation of harmonics using adaptive wavelet neural network
... In this paper the muliple layer feed forward neural network based adaptive wavelet neural network (AWNN) is implemented for estimating the harmonics. The proposed scheme is implemented ...
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Performance Improvement of GPS GDOP Approximation Using Recurrent Wavelet Neural Network
... One of the most important factors affecting the precision of the performance of a GPS receiver is the relative positioning of satellites to each other. Therefore, it is essential to choose appropriate accessible ...
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Wavelet Neural Network with Random Wavelet Function Parameters
... method. Wavelet functions in the hidden layer of the proposed network leads to a higher approximation ability in comparison with NNRW [13], and RVFL ...
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An auditory classifier employing a wavelet neural network implemented in a digital design
... form a vector of 2 n total length. The similarities also extend to the matrices involved in these calculations. The inverse transforms for both the DWT and FFT use the transpose of the matrix from the forward transform. ...
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An Enhanced Wavelet Neural Network Model For Epileptic Seizure Detection And Prediction
... the network design of RBFNs, WNNs also employ localized activation functions in the hidden nodes, where the locations of translation vectors need to be determined ...
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Network Intrusion Detection Using Self-Recurrent Wavelet Neural Network with Multidimensional Radial Wavelons
... of neural networks to the models of intrusion detection performs in a significant way, due to the fact that the three models considered (FRNN, SRWNN, SRWNNMRW) are located in the upper triangular ...
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Optimization of coded singals based on wavelet neural network
... a wavelet for activation instead of the classic sigmoidal ...characterizes neural networks. The nodes (or wavelons) of wavelet networks are wavelet coefficients of the function expansion that ...
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An Image Compression Method Based on Wavelet Transform and Neural Network
... excellent wavelet transform and the self-learning function of the traditional artificial nerual ...after wavelet decomposition have the property and classification characteristics of the common approximate ...
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Fault Detection and Diagnosis of Induction Machines based on Wavelet and Probabilistic Neural Network
... used neural networks in practical applications ...integrates wavelet with neural network and employed a novel training algorithm is proposed in this ...The wavelet neural ...
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A Lung Sound Category Recognition Method Based on Wavelet Decomposition and BP Neural Network
... given. Wavelet de-noised method is adopted to reduce noise of collected lung sounds and extract wavelet characteristic coefficients of the de-noised lung sounds by wavelet ...after wavelet ...
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Fusion of Multi Modal Lumber Spine Scans Using Wavelet and Convolutional Neural Network
... convolutional neural network that is trained on more than a million images from the ImageNetdatabase ...the network has learned rich feature representations for a wide range of ...The network ...
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