How to Install and Uninstall nest-doc.noarch Package on Fedora 34
Last updated: November 26,2024
1. Install "nest-doc.noarch" package
Please follow the instructions below to install nest-doc.noarch on Fedora 34
$
sudo dnf update
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$
sudo dnf install
nest-doc.noarch
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2. Uninstall "nest-doc.noarch" package
In this section, we are going to explain the necessary steps to uninstall nest-doc.noarch on Fedora 34:
$
sudo dnf remove
nest-doc.noarch
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$
sudo dnf autoremove
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3. Information about the nest-doc.noarch package on Fedora 34
Last metadata expiration check: 0:18:29 ago on Tue Sep 6 08:10:37 2022.
Available Packages
Name : nest-doc
Version : 3.2
Release : 4.fc34
Architecture : noarch
Size : 1.7 M
Source : nest-3.2-4.fc34.src.rpm
Repository : updates
Summary : Documentation for nest
URL : http://www.nest-simulator.org/
License : GPLv2+ and MIT and LGPLv2+
Description : NEST is a simulator for spiking neural network models that focuses on the
: dynamics, size and structure of neural systems rather than on the exact
: morphology of individual neurons. The development of NEST is coordinated by the
: NEST Initiative. NEST is ideal for networks of spiking neurons of any size,
: for example: Models of information processing e.g. in the visual or auditory
: cortex of mammals; Models of network activity dynamics, e.g. laminar cortical
: networks or balanced random networks; Models of learning and plasticity.
: Please read the README-Fedora.md file provided in each package for information
: on how these NEST packages are to be used.
:
: Please see https://nest-simulator.readthedocs.io/ for the latest documentation.
Available Packages
Name : nest-doc
Version : 3.2
Release : 4.fc34
Architecture : noarch
Size : 1.7 M
Source : nest-3.2-4.fc34.src.rpm
Repository : updates
Summary : Documentation for nest
URL : http://www.nest-simulator.org/
License : GPLv2+ and MIT and LGPLv2+
Description : NEST is a simulator for spiking neural network models that focuses on the
: dynamics, size and structure of neural systems rather than on the exact
: morphology of individual neurons. The development of NEST is coordinated by the
: NEST Initiative. NEST is ideal for networks of spiking neurons of any size,
: for example: Models of information processing e.g. in the visual or auditory
: cortex of mammals; Models of network activity dynamics, e.g. laminar cortical
: networks or balanced random networks; Models of learning and plasticity.
: Please read the README-Fedora.md file provided in each package for information
: on how these NEST packages are to be used.
:
: Please see https://nest-simulator.readthedocs.io/ for the latest documentation.