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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.


User guide available in HTML format from; Complete manual available in PDF format from; Complete manual also available in HTML from


Download version 1.1.0 (stable)
released on 20 April 2004

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LicenseVerified byVerified onNotes
LGPLv2.1orlaterJanet Casey10 December 2003

Leaders and contributors

Steffen Nissen Maintainer

Resources and communication

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Software prerequisites

This entry (in part or in whole) was last reviewed on 7 January 2008.


Permission is granted to copy, distribute and/or modify this document under the terms of the GNU Free Documentation License, Version 1.3 or any later version published by the Free Software Foundation; with no Invariant Sections, no Front-Cover Texts, and no Back-Cover Texts. A copy of the license is included in the page “GNU Free Documentation License”.

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