Browsing by Subject "Vector quantization"
Now showing items 1-6 of 6
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Conference Object
Comparative analysis of artificial neural network models: Application in bankruptcy prediction
(IEEE, 1999)This study compares the predictive performance of three neural network methods, namely the Learning Vector Quantization, Radial Basis Function, the Feedforward network that uses the conjugate gradient optimization algorithm, ...
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Article
Determination of the number of errors in DFT codes subject to low-level quantization noise
(2008)This paper analyzes the effects of quantization or other low-level noise on the error correcting capability of a popular class of real-number Bose-Chaudhuri-Hocquenghem (BCH) codes known as discrete Fourier transform (DFT) ...
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Conference Object
The effect of color correction of endoscopy images for quantitative analysis in endometrium
(2005)The objective of this study was to develop a standardized protocol for the capturing and analysis of endoscopy digital images for subsequent use in a Computer Aided Diagnosis (CAD) system in gynaecological cancer. Images ...
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Conference Object
Hybrid neural network electromyographic system: Incorporating the WISARD net
(IEEE, 1994)Clinical electromyography (EMG) provides useful information for the diagnosis of neuromuscular disorders. The utility of artificial neural networks trained with the backpropagation, the Kohonen's self-organizing feature ...
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Conference Object
New technique for the classification and decomposition of EMG signals
(IEEE, 1995)The shapes and firing rates of motor unit action potentials (MUAPs) in an electromyographic (EMG) signal provide an important source of information for the diagnosis of neuromuscular disorders. In order to extract this ...
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Conference Object
Non-stationary texture segmentation using an AM-FM model
(1997)We present a novel method for segmenting non-stationary textures. Our approach uses a multidimensional AM-FM representation for the texture, and provides the FM features to an SOFM-LVQ neural network system that performs ...