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2. Multilayer perceptron - Wikipedia

   en.wikipedia.org/wiki/Multilayer_perceptron

   In 1962, Rosenblatt published many variants and experiments on perceptrons in his book Principles of Neurodynamics, including up to 2 trainable layers by "back-propagating errors". [13] However, it was not the backpropagation algorithm, and he did not have a general method for training multiple layers.

3. Types of artificial neural networks - Wikipedia

   en.wikipedia.org/wiki/Types_of_artificial_neural...

   Radial basis functions are functions that have a distance criterion with respect to a center. Radial basis functions have been applied as a replacement for the sigmoidal hidden layer transfer characteristic in multi-layer perceptrons. RBF networks have two layers: In the first, input is mapped onto each RBF in the 'hidden' layer.

4. List of PDF software - Wikipedia

   en.wikipedia.org/wiki/List_of_PDF_software

   Export PDF and many other formats, multi-pages and multi-layers. Supports JS forms Cannot edit PDF Files. [3] Smallpdf Desktop: Proprietary: Yes Yes Yes Yes Supports merging, splitting, and extracting pages from PDFs. Also rotating, deleting and reordering pages. Converts PDF to Word, Excel, PowerPoint, raster images. Soda PDF: Proprietary: Yes ...

5. Perceptron - Wikipedia

   en.wikipedia.org/wiki/Perceptron

   For a single-layer perceptron with multiple output units, since the weights of one output unit are completely separate from all the others', the same algorithm can be run for each output unit. For multilayer perceptrons, where a hidden layer exists, more sophisticated algorithms such as backpropagation must be used.

6. Multilayer perceptrons - Wikipedia

   en.wikipedia.org/?title=Multilayer_perceptrons&...

   This page was last edited on 10 August 2023, at 11:09 (UTC).; Text is available under the Creative Commons Attribution-ShareAlike 4.0 License; additional terms may ...

7. Perceptrons (book) - Wikipedia

   en.wikipedia.org/wiki/Perceptrons_(book)

   What the book does prove is that in three-layered feed-forward perceptrons (with a so-called "hidden" or "intermediary" layer), it is not possible to compute some predicates unless at least one of the neurons in the first layer of neurons (the "intermediary" layer) is connected with a non-null weight to each and every input (Theorem 3.1.1 ...