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In social insects, workers perform a multitude of tasks such as foraging, nest construction and brood rearing without central control of how work is allocated among individuals. It has been suggested that workers choose a task by responding to stimuli gath ...
memory in biological neural networks. Similarly, artificial neural networks could benefit from modulatory dynamics when facing certain types of learning problem. Here we test this hypothesis by introducing modulatory neurons to enhance or dampen neural pla ...
This paper presents realization and the laboratory tests of the Kohonen winner takes all (WTA) neural network (NN) realized on microcontrollers (μC) with the AVR and ARM CortexM3 cores. Both μCs have been placed on a single testing board especially designe ...
The direction of others' eye gaze has important influences on how we perceive their emotional expressions. Here, we examined differences in neural activation to direct-versus averted-gaze fear faces as a function of culture of the participant (Japanese ver ...
The evolution of artificial neural networks (ANNs) is often used to tackle difficult control problems. There are different approaches to the encoding of neural networks in artificial genomes. Analog Genetic Encoding (AGE) is a new implicit method derived f ...
Quantization of the parameters of a Perceptron is a central problem in hardware implementation of neural networks using a numerical technology. A neural model with each weight limited to a small integer range will require little surface of silicon. Moreove ...
A growing number of neural networks are based on topologies that deviate from the standard fixed first order fully interlayer connected ones. Although there currently exist a variety of neural network simulators, few are flexible enough to facilitate subst ...
The backpropagation algorithm is widely used for training multilayer neural networks. In this publication the steepness of its activation functions is investigated. In specific, it is discussed that changing the steepness of the activation function is equi ...
All-optical multilayer perceptrons differ in various ways from the ideal neural network model. Examples are the use of non-ideal activation functions which are truncated, asymmetric, and have a non-standard gain, restriction of the network parameters to no ...
In order to assist the field of neural networks in maturing, a formalization and a solid foundation are essential. Additionally, to permit the introduction of formal proofs, it is essential to have an all- encompassing formal mathematical definition of a n ...
