Probabilistic neural networks
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Summary
A probabilistic neural network that can compute nonlinear decision boundaries which approach the Bayes optimal is formed, and a fourlayer neural network of the type proposed can map any input pattern to any number of classifications.
- Type
- article
- Published
- 1990-01-01
- Cited by
- 3,974
- References
- 13
- OpenAlex
- https://openalex.org/W1964168965
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:15189518
Keywords
Computer science, Artificial neural network, Sigmoid function, Activation function, Probabilistic neural network
References
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- Estimation of a multivariate density
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- Nearest neighbor pattern classification
- Probabilistic neural networks for classification, mapping, or associative memory
- Generation of Polynomial Discriminant Functions for Pattern Recognition
- An Introduction to the Theory of Statistics
- An Introduction to the Theory of Statistics
- Multivariate Analysis
- Parallel Distributed Processing Volume 1: Foundations
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- Klasifikasi Otomatis Kelompok Bintik Matahari Untuk Menganalisa Kondisi Cuaca Antariksa
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- Pattern recognition system for the discrimination of multiple sclerosis from cerebral microangiopathy lesions based on texture analysis of magnetic resonance images.
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- Comparison of two neural network classifiers in the differential diagnosis of essential tremor and Parkinson’s disease by 123I-FP-CIT brain SPECT
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- Prostate Tissue Characterization/Classification in 144 Patient Population Using Wavelet and Higher Order Spectra Features from Transrectal Ultrasound Images
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- A decision support system using classification of the blood glucose and HbA1C level classes from palm perspiration data
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