Free neural network software for linux

Neural Network Framework project is a C++ framework to develop, simulate, and analyze arbitrary complex neural networks.
The programmer can use the classes provided to create neural networks with arbitrary topology and mixed type of neurons. Its very easy to add customized neurons and layers.
Enhancements:
- A ScaleFunction that scales the input vector of a Cluster and a normalize method for RealVec were added.
- Two methods were added to the Random class to randomize RealVec and RealMat.

Fast Artificial Neural Network Library implements multilayer artificial neural networks in C with support for both fully connected and sparsely connected networks.
Cross-platform execution in both fixed and floating point are supported. It includes a framework for easy handling of training data sets. It is easy to use, versatile, well documented, and fast. PHP, Python, Delphi and Mathematica bindings are available.
Main features:
- Multilayer Artificial Neural Network Library in C
- Backpropagation training (RPROP, Quickprop, Batch, Incremental)
- Evolving topology training which dynamically builds and trains the ANN (Cascade2)
- Easy to use (create, train and run an ANN with just three function calls)
- Fast (up to 150 times faster execution than other libraries)
- Versatile (possible to adjust many parameters and features on-the-fly)
- Well documented (An easy to use reference manual, a 50+ page university report describing the implementation considerations etc. and an introduction article)
- Cross-platform (configure script for linux and unix, dll files for windows, project files for MSVC++ and Borland compilers are also reported to work)
- Several different activation functions implemented (including stepwise linear functions for that extra bit of speed)
- Easy to save and load entire ANNs
- Several easy to use examples (simple train example and simple test example)
- Can use both floating point and fixed point numbers (actually both float, double and int are available)
- Cache optimized (for that extra bit of speed)
- Open source (licenced under LGPL)
- Framework for easy handling of training data sets
- Graphical Interface
- C++ Bindings
- PHP Extension
- Python Bindings
- Delphi Bindings
- .NET Bindings
- Mathematica Extension
- Octave Extension
- Ruby Bindings
- Pure Data Bindings
- Debian package

GNOME Network is a set of client network-oriented tools, which currently contains a network information tool, a remote shell and desktop clients and a personal web server and a desktop sharing tool.
GNOME Network is Free Software distributed under the terms of the GNU GPL.
Enhancements:
Updated translations:
- gl (Ignacio)
- it (Alessio)

Pinger Network Tools is a simple frontend for ping, netstat, traceroute and whois.

My first ever Kommander script that I did in an effort to learn the Kommander scripting engine/style and to have something useful.

Built with Kommander Editor 1.2

Java Network Stack provides a Java library for research oriented network programming.

Java Network Stack is a library used by the DIMES project to create new internet measurements. It provides a clean API for packet manipulation, send, receive, filter, and analysis. It is a unification of raw socket capabilities, MAC level networkingm, and IPv6 capabilities.

gnetload network load meter project is a network and ISDN load meter that is similar to xisdnload, but works in a distributed environment.
It includes an agent (devstata) that runs on machines with interfaces to be monitored and periodically sends status information over the network. A display program (gnetload) collects and displays the data.
Both can be run on the same machine, or be used to report on the state of a dedicated router on another machine. Using multicast or broadcast addresses, data can be fed to more than one instance of gnetload. A menu for taking network interfaces up and down is also provided.
Usage: ./gnetload [-I] [-t tickscale] [-g geometry] [-d] [ip]:port
Enhancements:
- The config script was updated to build with GTK2 and GCONF2 where available.
- There are no other code changes.

AI::NeuralNet::BackProp is a simple back-prop neural net that uses Deltas and Hebbs rule.

SYNOPSIS

use AI::NeuralNet::BackProp;
# Create a new network with 1 layer, 5 inputs, and 5 outputs.
my $net = new AI::NeuralNet::BackProp(1,5,5);

# Add a small amount of randomness to the network
$net->random(0.001);

# Demonstrate a simple learn() call
my @inputs = ( 0,0,1,1,1 );
my @ouputs = ( 1,0,1,0,1 );

print $net->learn(@inputs, @outputs),"n";

# Create a data set to learn
my @set = (
[ 2,2,3,4,1 ], [ 1,1,1,1,1 ],
[ 1,1,1,1,1 ], [ 0,0,0,0,0 ],
[ 1,1,1,0,0 ], [ 0,0,0,1,1 ]
);

# Demo learn_set()
my $f = $net->learn_set(@set);
print "Forgetfulness: $f unitn";

# Crunch a bunch of strings and return array refs
my $phrase1 = $net->crunch("I love neural networks!");
my $phrase2 = $net->crunch("Jay Lenno is wierd.");
my $phrase3 = $net->crunch("The rain in spain...");
my $phrase4 = $net->crunch("Tired of word crunching yet?");

# Make a data set from the array refs
my @phrases = (
$phrase1, $phrase2,
$phrase3, $phrase4
);

# Learn the data set
$net->learn_set(@phrases);

# Run a test phrase through the network
my $test_phrase = $net->crunch("I love neural networking!");
my $result = $net->run($test_phrase);

# Get this, it prints "Jay Leno is networking!" ... LOL!
print $net->uncrunch($result),"n";

AI::NeuralNet::BackProp is the flagship package for this file. It implements a nerual network similar to a feed-foward, back-propagtion network; learning via a mix of a generalization of the Delta rule and a disection of Hebbs rule. The actual neruons of the network are implemented via the AI::NeuralNet::BackProp::neuron package

Network Probe and protocol analyzer is the ultimate tool for traffic-level network monitoring, troubleshooting, analysis,
If your network is crawling to a standstill, and you suspect there might be a problem with the network traffic, Network Probe will quickly help you identify what is causing the problem, show you who is generating any troublesome traffic, and where the traffic is being transmitted.
Network Probe will collect traffic statistics for all protocols, hosts, and conversations on your network, and show you all the top talkers and listeners on your network. Hosts generating large amounts of traffic such as music and movie streaming, playing online games, or listening to streaming media are easily identified.
Main features:
- Watch in real time which protocols are used on your network
- Watch in real time which hosts are active on your network and the Internet
- Watch in real time which conversations are taking place on your network and to and from the Internet
- Watch in real time detailed protocol statistics per host
- Watch in real time detailed protocol statistics per conversation
- Watch in real time network card details for your network
- Watch traffic amount of selected entries relative to the total and filtered traffic
- Watch traffic amount over time for any host, conversation, and protocol
- Watch in real time network throughput for the entire network segment
- Inspect detailed logged statistical data from days and weeks earlier
- Filter out and search for selected protocols, hosts, conversations, and network cards
- Sort network traffic by amount of data transmitted or received
- Export network traffic statistics data
- Configure users with restricted access to statistical data
- Password protected login