wavelet-based neural networks
Wavelet Based Neural Networks for Daily Stream Flow Forecasting
... the neural network uses the gradient descent method to modify the randomly selected weights of the nodes in response to the errors between the actual output values and the target ...
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Recognition of Power Transformer faults using Wavelet based Neural Networks
... Abstract- Recognition of Power-Transformer Protection is a veryimportant task for the power system operation. In this work, a hybrid of wavelet transform and neural network (WNN) approach is introduced for ...
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A Neuro-wavelet Method for the Forecasting of Financial Time Series
... [17]. Neural networks (NN), on the other hand, are data- driven self-adaptive methods that have the capability to extract essential parameters from complex high-dimensional ...a wavelet-based ...
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Emotional voice conversion using neural networks with arbitrary scales F0 based on wavelet transform
... Recently, the study of voice conversion (VC) has attracted wide attention in the field of speech processing. This technology can be applied in various domains, such as emotion conversion [1], speech assistance [2], and ...
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A Wavelet Neural Networks License Recognition Algorithm and Its Application
... Using wavelet transform to handle auto-mobile image with complex background for license localization, then preprocess license characters on vehicle licenses, and extracting the textural features of license ...
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Forecasting Baltic Dirty Tanker Index by Applying Wavelet Neural Networks
... designed for tanker shipping, the use of static models shows is of similar nature to that of Zanneto’s in analyz- ing the supply and demand in shipping by econometric explanation modeling methods. In contrast to static ...
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Research on the Robot Wrist Sensor Dynamic Characteristics Based on Improved Genetic Wavelet Neural Networks
... In experimental the training data is step response of the wrist force sensor. The Mexica hat wavelet function is selected as hidden neuron’s transform function of WNN. When the iterations evolution is 45 the error ...
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Image Denoising by Hybridizing Preprocessed Discrete Wavelet Transformation and Recurrent Neural Networks
... The feature extraction is a specific and salient feature for pattern recognition task. Therefore, to build the pattern information, encoding the pattern, the preprocessing is indispensable. Low-level feature extraction ...
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Dynamic evolution evoked by external inputs in memristor based wavelet neural networks with different memductance functions
... nonlinear neural networks have been re- ported, see ...memristor-based neural networks, to study the dynamic flows of these systems, the classical approach on nonlinear systemic theory ...
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Time Series Modeling of River Flow Using Wavelet Neural Networks
... An ANN, can be defined as a system or mathematical model consisting of many nonlinear artificial neurons running in parallel, which can be generated, as one or multiple layered. Although the concept of artificial neu- ...
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IDENTIFICATION AND CLASSIFICATION OF TEXTILE DEFECTS USING WAVELET FRAMES AND NEURAL NETWORKS
... classification based on computer ...module wavelet frames, gabor filter, PCA are ...neural networks. In particular, the proposed system is carried out using wavelet frames, gabor ...
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Discrete Wavelet Transforms and Artificial Neural Networks for Recognition of Isolated Spoken Words
... speech- based studies are based on Fourier Transforms (FTs), Short Time Fourier Transforms (STFTs), Mel-Frequency Cepstral coefficients (MFCCs), Linear predictive Coding (LPCs), and prosodic ...
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Legendre Wavelet Neural Networks for Power Amplifier Linearization
... Legendre wavelet neural networks (LWNN) is first utilized to model PA and inverse structure of the PA by applying practical transmission signals and the gradient descent algorithm is applied to ...
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Power Disturbance Recognition Using Probabilistic Neural Networks
... recognizer, wavelet-based Probabilistic Neural Network, presented in this work is designed to recognize seven types of power quality disturbances, such as flicker, harmonics, interrupt, pure sine ...
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BLOCK FEATURE BASED IMAGE FUSION USING MULTI WAVELET TRANSFORMS
... feature based image fusion is implemented using multi wavelet transform and neural networks and a qualitative analysis has been done for the several test image and found better ...
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The Most General Intelligent Architectures of the Hybrid Neuro-Fuzzy Models
... Hybrid neural networks – based systems, are based on an architecture which integrates the neural networks and the fuzzy logic based system in the form of parallel ...the ...
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A Study of Textural Analysis Methods for the Diagnosis of Liver Diseases from Abdominal Computed Tomography
... Neural networks have been extensively used in pattern classification applications. CT liver images are characterized into normal, visible and invisible malignancy [9]. Three different sets of statistical ...
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Method of Wireless Sensor Network Data Fusion
... In this paper, MATLAB simulation software is used to simulate the RBF neural network. The simulated training data are selected from the values of the groundwater level, channel flow, air temperature, saturation ...
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Optimized Image Compression through Artificial Neural Networks and Wavelet Theory
... The compression results vary for the different images because number of bits that are required to represent an image differs for all three images, but all images shows better compression performance when wavelets are ...
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THE ROLE OF INFORMATION TECHNOLOGY ON THE GROWTH OF FIRMS: A VALUE ADDED ONSIDERATION
... Web applications are useful to share the general and specific information and to do many business activities globally, usingthe internet. The most important component of these applications is the web pages. A web page is ...
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