In this paper, a comparison study for phishing detection between two neural networks which are the feedforward neural network and the deep learning neural network is carried out. The result is empirically evaluated to determine which method performs better in phishing detection....
About A simple feedforward neural network written in purely C. License GPL-3.0 license Activity Stars 0 stars Watchers 1 watching Forks 0 forks Report repository Releases No releases published Packages No packages published Languages C 99.5% Batchfile 0.5% Footer...
Genann is a minimal, well-tested library for training and using feedforward artificial neural networks (ANN) in C. Its primary focus is on being simple, fast, reliable, and hackable. It achieves this by providing only the necessary functions and little extra....
This paper shows that a well-known causal PD controller plus feedforward solves the global output feedback tracking control problem of robot manipulators, by requiring only the existence of the robot natural damping, no matter how small. To this end, we first demonstrate that a robot controlled...
[4].IndividualunitsintheirnetworkreceiveisotropicfeedforwardinputfromthegeniculateandrecurrentconnectionsfromneighboringunitsinaMexicanhatprofile,describedbyshort-rangeexcitationandlong-rangeinhibition.Iftherecurrentconnectionsaresufficientlystrong,hotspotsofactivity(or‘bumps’)formperiodicallyacrossspace.Inahomogeneousnetwork...
Feedforward Neural NetworkDeep Learning Neural NetworkPhishing attack is one of wide spread cybercrimes due to the advancement of the Internet. There are many forms of phishing attack and the most common one is through email. The attacker tries to pretend by sending email from an official ...
Here we present another non-iterative approach, Feedforward Convolutional Conceptor Neural Network (FCCNN), for training feedforward networks on image classification tasks. Our work makes two major contributions: (1) a conceptor based classifier which is specific for non-temporal data; (2) a ...
The universal approximation property of feedforward neural networks (FNNs) is the basis for all FNNs applications. In almost all existing FNN approximation studies, it is always assumed that the activation function of the network satisfies certain conditions, such as sigmoid or bounded continuity. ...
The universal approximation property of feedforward neural networks (FNNs) is the basis for all FNNs applications. In almost all existing FNN approximation studies, it is always assumed that the activation function of the network satisfies certain conditions, such as sigmoid or bounded continuity. ...
Adding lateral inhibition to a simple feedforward network enables it to perform exclusive-or. Smith L S. Neural Computation . 1998Smith L S. Adding lateral inhibition to a simple feedforward network enables it to perform exclusive-or[J].Neural Computation,1998,(02):277-277....