Implements multilayer feedforward ANNs much faster than other libraries
Fast Artificial Neural Network Library (fann) implements multi-layer feedforward networks that support both fully connected and sparsely connected networks. It supports execution in fixed point arithmetic to allow for fast execution on systems with no floating point processor. To overcome the problems of integer overflow, the library calculates a position of the decimal point after training and guarantees that integer overflow cannot occur with this decimal point. FANN is designed to be fast, versatile, and easy to use. Several benchmarks have been executed to test its performance. It is significantly faster than other libraries on systems without a floating point processor, and comparable to other highly optimized libraries on systems with a floating point processor.
DocumentationUser guide available in HTML format from http://fann.sourceforge.net/report/node7.html; Complete manual available in PDF format from http://prdownloads.sourceforge.net/fann/fann_doc_complete_1.0.pdf?download; Complete manual also available in HTML from http://fann.sourceforge.net/report/report.html
released on 24 January 2012
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|LGPLv2.1orlater||Janet Casey||10 December 2003|
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This entry (in part or in whole) was last reviewed on 25 February 2017.
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