adaptive probabilistic neural network
Adaptive complex modified probabilistic neural network in digital channel equalization
... ADAPTIVE COMPLEX MODIFIED PROBABILISTIC NEURAL NETWORK IN DIGITAL CHANNEL EQUALIZATION.. James P.[r] ...
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An Analysis of Hardware Configurations for an Adaptive Weightless Neural Network
... of neural network on mathematical logic ...Enhanced probabilistic Convergent Networks ...forward neural networks incorporating supervised learning with the addition that the mathematical logic ...
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Voltage stability analysis of load buses in electric power system using adaptive neuro fuzzy inference system (ANFIS) and probabilistic neural network (PNN)
... artificial neural network (ANN) in voltage stability ...(MLPBP) neural network, adaptive neuro-fuzzy inference system (ANFIS) and probabilistic ...
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Hybrid Feature Description with Probabilistic Neural Network for Adaptive Face Recognition with Angular Variance
... ABSTRACT: The features descriptors describe the data from the images in the form of the low level features, color based features, matrix quality or matrix representation thresholds, texture based feature or binary ...
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Identification and Adaptive Control of Dynamic Nonlinear Systems Using Sigmoid Diagonal Recurrent Neural Network
... new neural network architecture called based on the adaptation of the shape of the sig- moid weight of the hidden layer neurons and have intro- duced its corresponding dynamic back propagation learning ...
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Detection of Network Intrusion Threat Based on the Probabilistic Neural Network Model
... the network at a low cost without professional knowledge ...malicious network attacks. Therefore, network intrusion detection is getting more and more attention with the development of ...to ...
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Support Vector Machine Neural Network Based Optimal Binary Classifier for Diabetic Retinopathy
... Lisoba, Ifeachor and Szczepaniak describe variations in biomedical data which are affected by factors such as medication, environmental conditions, age, weight, mental and physical state. Consequently, clinical ...
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Research of adaptive control algorithm research based on rough set and implementation
... an adaptive neural network algorithm has strong compatibility, some noise data, not including related function and reduce the input dimension, a fast learning process, uncertainty processing and ...
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Face Recognition using Probabilistic Model for Locally Changed Face
... a probabilistic approach that is simple but effective for face recognition problems ...determines probabilistic parameter, when the data has missing values. Neural Network Classifier recognize ...
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A chemical-reaction-optimization-based neuro-fuzzy hybrid network for stock closing price prediction
... and probabilistic theories, which can handle only dichotomous or Boolean ...of neural net- works with the human-like logical reasoning capability of fuzzy systems, thereby taking advantage of both aspects ...
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Brain Tumor Classification using Probabilistic Neural Network
... paper, Probabilistic Neural Network with image and data processing techniques was employed to implement an automated brain tumor ...the Probabilistic Neural Network ...
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Training and classification of Epilepsy Detection using EEG
... other neural networks today use gradual linear progression functions to ease an NN into its proper behavior, some researchers use genetic algorithms to evolve ...
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Neural Network and Adaptive Feature Extraction Technique for Pattern Recognition
... PCA Feature Extraction by Hebbian Algorithm The principal component analysis (PCA) is a Multivariate Statistical Process Control (MSPC) methods. Feature extraction methods determine an appropriate subspace of ...
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Modified probabilistic neural network hardware implementation schemes
... equation (4). The first design is a virtual digital design and the second a fully parallel design. This RBF selects training centres which are within a specified c[r] ...
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The modified probabilistic neural network as a nonlinear correlator detector
... A neural network can be developed to embody this model and provide a continuous nonlinear correlator output r(x) as the vector x is taken from the process signal by sliding [r] ...
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Probabilistic Neural Network Assisted Cell Tracking and Classification
... the key actors in many biological processes. Even today, some of the cell tracking problems are dense populations of cells, presence of complex behavior or poor image quality. The existing cell tracking methods are ...
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Face Detection Using Probabilistic Neural Network (PNN)
... Probabilistic neural networks can be used for classification problems (i.e. face detection). When an input is presented, the first layer computes distances from the input vector to the training input ...
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Intelligent Decision Support Systems for Oil Price Forecasting
... However, very few consider both regular factors and uncertain events. For example, Yu et al. (2005) used rules-based expert systems to forecast the price volatility of crude oil based on significant factors that affect ...
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Center reduction algorithm for the modified probabilistic neural network equalizer
... (2001) Center reduction algorithm for the modified probabilistic neural network equalizer.. In: Proceedings of the International Joint.[r] ...
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Classification of aircraft images using different architectures of radial basis function neural network : a performance comparison
... classification performance of Goal Oriented Radial Basis Architecture, Generalized Gaussian. Neural Network Architecture and Probabilistic Neural Network Architecture is [r] ...
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